machine learning architect

NewRocket

<div>Agentic AI Architect-Anthropic Partnership

Why Us

NewRocket is proud Anthropic partner/vendor, expanding our ability to help enterprises responsibly adopt and operationalize Claude-powered AI solutions. Through this relationship, NewRocket is building advanced capabilities in generative AI, agentic workflows, secure enterprise knowledge experiences, and AI-enabled automation. Our teams apply Anthropic-aligned practices in prompt and context engineering, retrieval-augmented generation (RAG), tool use, structured outputs, model evaluation, safety, governance, and human-in-the-loop controls.

For an Agentic AI Architect, this partnership represents an opportunity to work at the forefront of enterprise AI&mdash;designing scalable, secure, and high-value solutions that connect Claude and other AI technologies with ServiceNow, enterprise data, business processes, and mission-critical workflows.

NewRocket is the AI-first Elite ServiceNow Partner that activates real value on the Now Platform. As a trusted advisor to enterprise leaders, we combine industry expertise, human-centered design, and enterprise-grade AI to help organizations navigate change and scale with confidence.

Travel to clients and conferences as needed.

We #GoBeyondWorkflows to create new kinds of experiences for our customers.

Come join our Crew!

The Role

NewRocket is hiring an experienced Agentic AI Architect to support a large global client and help shape, design, and deploy enterprise AI solutions.

This role combines AI/ML architecture, generative AI engineering, data engineering, cloud solution design, and technical leadership. You will be responsible for defining scalable architectures for AI and machine learning applications, including predictive analytics, natural language processing, retrieval-augmented generation (RAG), intelligent automation, and agentic AI systems.

The ideal candidate brings strong hands-on expertise in Python, SQL, cloud services, databases, big-data technologies, and modern machine learning frameworks. You will also have practical experience designing LLM-powered applications that safely connect models to enterprise knowledge, systems, APIs, and workflows.

You will work closely with client stakeholders, NewRocket consultants, ServiceNow teams, data engineers, and AI/ML engineers to translate business needs into secure, reliable, and production-ready AI solutions.

We are #GoingBeyond. Come join our Crew!

What You Will Be Doing

AI/ML Architecture &amp; Solution Delivery
<ul>
<li>Architect, develop, deploy, and maintain scalable AI and machine learning solutions for enterprise use cases.</li>
<li>Define end-to-end solution architectures spanning data ingestion, data preparation, model selection, orchestration, APIs, workflow integrations, user experiences, monitoring, and governance.</li>
<li>Partner with business and technical stakeholders to identify high-value AI opportunities and translate requirements into actionable technical designs and delivery roadmaps.</li>
<li>Design solutions for predictive analytics, classification, clustering, forecasting, anomaly detection, recommendation, and intelligent automation.</li>
<li>Establish technical standards, reference architectures, reusable patterns, and best practices for enterprise AI delivery.</li>
<li>Lead technical discovery, architecture workshops, design reviews, proof-of-concepts, and client demonstrations.</li>
</ul>
Generative AI, Anthropic &amp; LLM Engineering
<ul>
<li>Design and implement enterprise generative AI applications using Claude, the Anthropic API, and other LLM platforms when appropriate for the business use case.</li>
<li>Apply effective prompt and context-engineering practices, including instruction design, few-shot examples, role definition, structured inputs and outputs, response constraints, and long-context management.</li>
<li>Architect retrieval-augmented generation (RAG) solutions that securely ground model outputs in approved enterprise documents, knowledge bases, databases, and other data sources.</li>
<li>Design document ingestion, chunking, embedding, vector search, retrieval, reranking, citation, and response-generation patterns for enterprise knowledge workflows.</li>
<li>Build and integrate AI capabilities using structured outputs, tool use/function calling, APIs, and workflow orchestration.</li>
<li>Assess and recommend the appropriate balance of LLMs, traditional machine learning, deterministic automation, enterprise search, and human decision-making for each use case.</li>
<li>Stay current on Anthropic platform capabilities, Claude releases, Anthropic implementation guidance, responsible AI principles, and enterprise AI best practices.</li>
<li>Complete relevant Anthropic partner enablement, technical training, and product education as available through NewRocket's partnership.</li>
<li>Travel to clients and conferences as needed.</li>
</ul>
Agentic AI &amp; Workflow Orchestration
<ul>
<li>Architect and implement agentic AI systems that can reason over enterprise context, use authorized tools, execute multi-step tasks, and coordinate work across enterprise applications.</li>
<li>Design AI agents with defined roles, task boundaries, tool permissions, memory and context strategies, approval gates, fallback paths, and escalation mechanisms.</li>
<li>Develop agentic workflows that integrate with ServiceNow, enterprise APIs, cloud services, databases, collaboration platforms, and operational systems.</li>
<li>Implement human-in-the-loop controls for sensitive, high-impact, low-confidence, or exception-based actions.</li>
<li>Design safeguards to prevent unintended tool execution, unauthorized data access, prompt injection, unsafe outputs, and uncontrolled autonomous behavior.</li>
<li>Evaluate agent effectiveness through task-completion rates, quality, reliability, latency, cost, safety, and user-adoption measures.</li>
</ul>
Machine Learning, NLP &amp; Data Science
<ul>
<li>Develop, train, validate, deploy, and monitor machine learning models for predictive analytics, classification, clustering, and related use cases.</li>
<li>Implement AI and ML solutions using frameworks such as TensorFlow, PyTorch, and Scikit-learn.</li>
<li>Develop NLP capabilities using Hugging Face transformer models and cloud AI services for text classification, summarization, sentiment analysis, entity extraction, and document intelligence.</li>
<li>Evaluate, adapt, and where appropriate fine-tune open-source or client-approved models for targeted use cases; apply prompt engineering, RAG, and tool use as preferred strategies when model fine-tuning is not appropriate or available.</li>
<li>Work with large language models for conversational AI, text generation, summarization, knowledge assistance, workflow automation, and decision support.</li>
<li>Build data-processing and feature-engineering pipelines that support reliable model training, testing, deployment, and monitoring.</li>
</ul>
Cloud, Data Engineering &amp; Platform Integration
<ul>
<li>Design and implement AI solutions using cloud platforms including AWS (e.g., SageMaker, Lambda, S3), Microsoft Azure, and Google Cloud Platform (e.g., Vertex AI).</li>
<li>Develop integrations between AI services, ServiceNow, enterprise applications, APIs, identity providers, databases, document repositories, and data platforms.</li>
<li>Build supporting services, APIs, microservices, automation logic, and integration components required to operationalize AI solutions.</li>
<li>Work with big-data technologies such as Apache Spark and Snowflake for large-scale data processing, analytics, and AI data pipelines.</li>
<li>Design and optimize ETL/ELT pipelines for data ingestion, transformation, validation, quality management, governance, and observability.</li>
<li>Use SQL, MySQL, PostgreSQL, MongoDB, and comparable technologies for data modeling, database management, query optimization, and data warehousing.</li>
<li>Apply secure engineering practices for authentication, authorization, secrets management, encryption, logging, error handling, and access controls.</li>
</ul>
AI Quality, Governance &amp; Responsible AI
<ul>
<li>Establish evaluation frameworks, test suites, representative datasets, and regression-testing practices for AI, ML, and agentic solutions.</li>
<li>Measure and optimize solution quality across relevance, accuracy, groundedness, safety, task completion, model behavior, latency, cost, reliability, and user experience.</li>
<li>Implement observability, monitoring, tracing, alerting, and feedback loops for production AI applications.</li>
<li>Define practical governance approaches for data privacy, sensitive-data handling, model access, auditability, model limitations, and responsible AI usage.</li>
<li>Implement controls for role-based access, data permissions, grounded responses, source attribution, output validation, exception handling, and human review.</li>
<li>Document architecture decisions, AI-system behavior, limitations, risk controls, operating procedures, and support requirements.</li>
</ul>
ServiceNow, Automation &amp; Enterprise Experience
<ul>
<li>Design AI-enabled workflow automations and intelligent experiences within ServiceNow and connected enterprise ecosystems.</li>
<li>Support chatbot, virtual-agent, employee-support, customer-service, IT operations, knowledge-management, and workflow-automation use cases.</li>
<li>Integrate AI solutions with ServiceNow capabilities such as workflow automation, IntegrationHub, Flow Designer, Virtual Agent, Now Assist, AI Agents, knowledge management, and enterprise data sources, where applicable.</li>
<li>Develop AI automation solutions using collaboration platforms and cloud AI services, including Microsoft Teams and Azure AI, where appropriate.</li>
<li>Contribute reusable implementation patterns, agent designs, integration components, evaluation assets, and accelerators that strengthen NewRocket's AI Foundry capabilities.</li>
</ul>
Analytics &amp; Visualization
<ul>
<li>Create interactive data visualizations and executive-ready reporting using tools such as Tableau and Power BI.</li>
<li>Develop dashboards and measurement frameworks that help stakeholders understand AI adoption, workflow outcomes, business value, operational performance, and model quality.</li>
<li>Support the definition and tracking of KPIs that demonstrate measurable value from AI-enabled solutions.</li>
</ul>
What You Bring Along
<ul>
<li>10+ years of experience applying AI, machine learning, data science, software engineering, or intelligent automation technologies to practical enterprise use cases.</li>
<li>Strong coding expertise in Python and SQL, with hands-on experience using ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.</li>
<li>Demonstrated experience architecting or delivering AI/ML, LLM, RAG, conversational AI, agentic AI, or AI-powered automation solutions.</li>
<li>Strong understanding of algorithms, object-oriented programming, functional design principles, software architecture, and API-based integration patterns.</li>
<li>Hands-on experience with LLM concepts and application-development patterns, including prompt engineering, context management, tokens, embeddings, vector search, RAG, tool use, structured outputs, and model evaluation.</li>
<li>Proficiency with data-science libraries such as Pandas, NumPy, Matplotlib, and Seaborn.</li>
<li>Hands-on experience with cloud platforms such as AWS, Azure, and/or Google Cloud.</li>
<li>Experience with big-data processing and cloud data platforms, including Apache Spark and Snowflake.</li>
<li>NLP experience using Hugging Face, transformer models, cloud AI services, or comparable technologies.</li>
<li>Strong understanding of database management, query optimization, data warehousing, ETL/ELT pipelines, and data-quality practices.</li>
<li>Experience with data visualization tools such as Tableau and Power BI.</li>
<li>Knowledge of responsible AI practices, including privacy, security, human oversight, hallucination mitigation, prompt-injection defenses, model limitations, and governed deployment.</li>
<li>Strong analytical, architectural, problem-solving, communication, and stakeholder-management skills.</li>
<li>Ability to collaborate effectively across client, consulting, engineering, product, data, and AI/ML teams.</li>
<li>Ability to learn and adapt quickly as AI technologies, enterprise requirements, and client needs evolve.</li>
</ul>
Preferred Qualifications

Anthropic &amp; Claude Experience
<ul>
<li>Hands-on experience with Claude, the Anthropic API, Anthropic Console, Claude Code, or Anthropic-focused implementation guidance.</li>
<li>Completion of Anthropic Academy courses, partner enablement, technical training, or equivalent experience building Claude-powered enterprise applications.</li>
<li>Experience using Claude capabilities such as long-context processing, document analysis, tool use, structured outputs, and enterprise knowledge workflows.</li>
<li>Familiarity with Model Context Protocol (MCP) concepts and secure patterns for connecting AI applications to enterprise tools and data sources.</li>
</ul>
Agentic AI &amp; LLM Operations
<ul>
<li>Experience designing AI agents, multi-agent systems, AI orchestration workflows, and human-in-the-loop operating models.</li>
<li>Experience with LLM application frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or comparable frameworks.</li>
<li>Experience with vector databases, semantic retrieval, enterprise search, embeddings, document ingestion, reranking, and RAG evaluation.</li>
<li>Familiarity with AI observability, tracing, prompt/version management, evaluation frameworks, guardrails, model monitoring, and cost optimization.</li>
<li>Experience with MLOps, LLMOps, CI/CD, Docker, Kubernetes, infrastructure as code, and production cloud deployment practices.</li>
</ul>
Education
<ul>
<li>Bachelor's degree in Computer Science, Data Science, Artificial Intelligence/Machine Learning, Engineering, or a related technical field; equivalent relevant experience will also be considered.</li>
<li>Advanced degree or relevant AI, cloud, data, ServiceNow, or Anthropic certifications are a plus.</li></ul> 


We Take Care of Our People

NewRocket is committed to a diverse and inclusive workplace. We value and celebrate diversity, believing that every employee matters and should be respected and heard. We are proud to be an equal opportunity workplace and affirmative action employer, committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin, or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, citizenship, military, or Veteran status. For individuals with disabilities who would like to request an accommodation, please contact hr.in@newrocket.com.</div>

Agentic AI Architect-Anthropic-UK

North Oil Company Qatar

<div>
 Job description:
 
 
 
 Key Accountabilities
 
 
 &nbsp;
 
 
 
 This will be a definite term contract for 3 years.
 
 
 
 &nbsp;
 
 
 
 Evaluate, test, design and enable technology selection and implementation approach to improvement and optimize&nbsp; capabilities and data architecture (including AI &amp; ML) and design of agentic and autonomous AI solutions for enterprise&nbsp; use cases (covering POC, scale-up, and production&nbsp; deployment)
 
 
 <ul>
 <li>
 Evaluate, test, and design end to end data and AI architectures for enterprise and agentic use cases, covering POC, scale up, and production deployment.
 </li>
 <li>
 Architect enterprise data platforms optimized for AI, ML, and LLM integration and inference at scale.
 </li>
 <li>
 Define AI ready data architecture patterns supporting&nbsp; fine tuning, retrieval augmented generation, and prompt engineering workflows.
 </li>
 <li>
 Design hybrid architectures integrating on premises&nbsp; and cloud based LLM services with enterprise data platforms.
 </li>
 <li>
 Define reference patterns for multi model AI&nbsp; environments operating on shared and governed data.&nbsp;
 </li>
 <li>
 Design semantic layers, indexing, and similarity search for low latency AI workloads.
 </li>
 <li>
 Design enterprise knowledge graph architectures to&nbsp; support reasoning and contextual understanding.
 </li>
 <li>
 Define architectural mechanisms for data refresh,&nbsp; accuracy, relevance, and observability of retrieval performance and latency.
 </li>
 <li>
 Design multi agent architectures for cross functional workflows, including decision logic, tool usage, and&nbsp; interaction patterns for autonomous agents such as&nbsp; &nbsp;Microsoft Fabric Data Agent and Operational Agent.
 </li>
 <li>
 Design guardrails, auditability, and control mechanisms for agent actions, including feedback loops for continuous improvement.
 </li>
 <li>
 Define prompt orchestration patterns for multi-step&nbsp; reasoning aligned with NOC standards.
 </li>
 <li>
 Assess AI models, platforms, and tools using defined evaluation criteria and benchmarking, including proprietary, commercial, and open source options.
 </li>
 <li>
 Review and provide guidance on AI, ML, and advanced analytics architecture artefacts from vendors.
 </li>
 </ul>
 
 Job Purpose
 
 
 Responsible for designing and advancing data solutions that strengthen NOC data architecture and evaluating the adoption of emerging technologies within DBS, with a focus on AI, machine learning, and advanced analytics. The role requires deep expertise in Data &amp; AI Architecture /Engineering, cloud platforms,&nbsp;and integration patterns, combined with strong Oil &amp; Gas domain knowledge. It aims to enhance enterprise analytics capabilities by integrating AI/ML models and large-scale data processing frameworks to enable data-driven decision-making and improve operational efficiency.&nbsp;
 
 
 Key Accountabilities:
 
 <ul>
 <li>
 Evaluate, test, design and enable technology selection and implementation approach to improvement and optimize capabilities and data architecture (including AI &amp; ML) and design of agentic and autonomous AI solutions for enterprise use cases (covering POC, scale-up, and production deployment)
 </li>
 <li>
 Provide architectural guidance for data integration, ingestion patterns across enterprise data platforms and advanced analytics solutions in alignment with data modelling and MDM standards
 </li>
 <li>
 Design solutions in alignment with DBS best practices&nbsp; on Data and AI governance, information security controls, EA and PMO standards
 </li>
 <li>
 Review solutions and demands impacting Data Management part of Architecture Review Board (ARB)
 
 meetings
 </li>
 </ul>
 
 Key Accountabilities
 
 
 
 Provide architectural guidance for data integration, ingestion patterns across enterprise data
 
 
 platforms and advanced analytics solutions in alignment with data modelling and MDM standards
 
 
 <ul>
 <li>
 &nbsp;Design batch and streaming or real time ingestion and integration patterns aligned with NOC standards,&nbsp;
 
 including Integration Design Documents and design first principles.
 </li>
 <li>
 Define medallion, Kappa, and Lambda architectures as reference patterns.
 </li>
 <li>
 Maintain NOC data architecture for data platforms,&nbsp; digital use cases, demands, and data solutions.&nbsp;
 </li>
 <li>
 Document reference architectures and standard&nbsp; solution patterns for data and AI solutions, including&nbsp; IDD, HLD, LLD, dashboards and reports, model representations, data dictionaries, and data models&nbsp; such as CDM,LDM, and PDM.&nbsp;
 </li>
 <li>
 Ensure alignment of MDM principles with analytics and AI data requirements.
 </li>
 <li>
 Design data pipelines supporting continuous model training, evaluation, deployment, and retraining.
 </li>
 <li>
 Design CI and CD flows for ML models with monitoring for accuracy, latency, and cost.
 </li>
 <li>
 Design cost efficient inference and fine-tuning&nbsp; pproaches with usage tracking and controls..
 </li>
 </ul>
 
 
 Design solutions in alignment with DBS best practices on Data and AI governance, information security controls, EA and PMO standards
 
 
 <ul>
 <li>
 Support alignment with data and AI governance to ensure trusted and well governed data usage across&nbsp;
 
 platforms and advanced analytics.
 </li>
 <li>
 Design privacy preserving architectures for model&nbsp; training and fine tuning.
 </li>
 <li>
 Support definition of security controls and access patterns for data and AI platforms.
 </li>
 </ul>
 
 
 Review solutions and demands impacting Data Management part of Architecture Review Board (ARB) meetings
 
 
 <ul>
 <li>
 &nbsp;Support Architecture Review Board and Design Advisory sessions for data, AI, and ML solution reviews and approvals.
 </li>
 <li>
 Support delivery teams through architecture reviews and structured feedback on design artefacts.
 </li>
 <li>
 Identify and review reference solutions, architectures, and case studies to improve NOC architecture.
 </li>
 <li>
 Provide technical guidance to data operations, data governance, and related teams as required.
 </li>
 </ul>
 Competencies Delegate Appropriately and Communicate Effectively Demonstrate Adaptability in Managing Complex Situations Demonstrate Learning Agility and Drive Innovation Develop Emotional Intelligence and Cultural Competence Develop Others and Institutionalise Knowledge Develop Talent for the Future NOC Sustainability Facilitate Collaboration and Sense of Community Improve Safety, Technical Proficiency and Results Lead By Example with NOC Values Set Purpose, Strategic Direction and Company Plan Strengthen Accountability and Continuous Improvement Think and Act in Stakeholder-Centric Ways
 
 Education
 
 
 &nbsp;
 
 <ul>
 <li>
 Bachelor of Computer Science or Computer Engineering or relevant degree
 </li>
 <li>
 Specialization and certification in AI, ML engineering and/or Data Science.
 </li>
 </ul>
 
 Experience
 
 
 &nbsp;
 
 <ul>
 <li>
 Minimum of 8 years relevant experience in technical implementation of AI solutions. Designing data architectures, developing AI models, and ensuring the technical robustness of AI systems.
 </li>
 <li>
 Experience with machine learning techniques, such as Supervised/Unsupervised Learning, Deep Learning (e.g., Neural Networks, CNNs, RNNs), Natural Language&nbsp; Processing (NLP), Computer Vision and Text Analytics
 </li>
 <li>
 Hands on Experience with data agents, operational agent and Agentic AI
 </li>
 <li>
 Proven track record of delivering successful AI /Data digital products in the industry.
 </li>
 </ul>
 
 
 Job-Specific Skills (Generic / Technical):
 
 
 <ul>
 <li>
 Experience in AI Ready Data platforms &amp; Data architecture and data engineering foundation, technical
 
 implementation of AI solutions. Designing data&nbsp; architectures, developing AI models, and ensuring the
 
 technical robustness of AI systems.
 </li>
 <li>
 Strong understanding of software development life cycle (SDLC) and DevOps Practices.
 </li>
 <li>
 Strong hands-on Experience in AI and ML architecture, including Agentic and autonomous AI &amp; ML Ops Life cycle includes running POC to scale up solutions&nbsp;
 </li>
 <li>
 Strong Experience of design pipelines for model&nbsp; training, evaluation, and retraining including CI/CDD
 </li>
 <li>
 Excellent problem-solving skills and attention to detail.
 </li>
 <li>
 Strong communication and teamwork abilities.
 </li>
 <li>
 Ability to work independently.
 </li>
 <li>
 Experience with agile tools and software, such as Jira, Confluence, or similar.
 </li>
 <li>
 Experience on Projects using Industry Data Platforms (such as OSDU or Cognite Date Fusion) would be a plus
 </li>
 </ul>
</div>

Data Architect

Expleo Group

<div>Overview:
<div>
Expleo is the home of bold and reliable minds. With more than 50 years of experience in developing complex products, optimising manufacturing processes, and ensuring the quality of information systems, Expleo boasts an extensive global footprint, powered by 19,000 highly skilled experts delivering value in 30 countries.</div><div></div><div> 
Our efforts in creating a supportive and inclusive workplace in India have earned us some key recognitions:</div> 
<div></div><ul><li>
'Great Place to Work' certification for building a supportive, engaging environment.</li><li>
'Progressive Place to Work,' by ET Now, for our dedication to innovation and inclusive workplace policies.</li><li>
'Best Organizations for Women,' by ET Now, for empowering women by providing equal opportunities, supporting professional development and promoting inclusive leadership.</li></ul>
Responsibilities:
<ul><li>Presales &amp; Solutioning</li><li>
Lead the AI/ML solutioning during presales engagements by assessing client requirements, conducting feasibility analysis, and identifying the right-fit technology stack.</li><li>
Create solution architectures, conceptual models, and high-level designs aligned to client business goals.</li><li>
Collaborate with sales teams to drive customer conversations, technical workshops, and demos.</li><li>
Respond to RFPs/RFIs and develop compelling proposals, effort estimates, and technical presentations.</li><li>
Translate complex AI concepts into business language for diverse stakeholders, including CXOs.</li><li>
Offer Development &amp; Go-to-Market (GTM)</li><li>
Develop and package AI solution offerings tailored to industry use cases (e.g., predictive maintenance, customer intelligence, document automation, anomaly detection).</li><li>
Partner with product and marketing teams to define go-to-market strategies, value propositions, and sales collateral.</li><li>
Stay updated on emerging trends in AI/ML, GenAI, MLOps, LLMs, and related ecosystems to ensure competitive positioning of offerings.</li><li>
Support internal capability building by defining solution blueprints, reusable assets, and reference architectures.</li><li>
Act as a trusted advisor to clients on AI-driven digital transformation initiatives.</li><li>
Participate in initial project mobilization, ensuring smooth hand-off to delivery teams with a clear understanding of solution architecture, risks, and assumptions.</li><li>
Support POCs, pilots, and MVPs to validate solution hypotheses and drive stakeholder buy-in.</li></ul>
Qualifications:
<div>
Bachelor&rsquo;s or Master&rsquo;s in Computer Science, Data Science, Engineering, or related field.</div> 
<div></div>
Essential skills:
<ul><li>Deep knowledge of machine learning, deep learning, NLP, LLMs, and MLOps pipelines.</li><li>
Experience with cloud AI/ML platforms (AWS Sagemaker, Azure ML, Google Vertex AI).</li><li>
Proficiency in Python, ML libraries (scikit-learn, TensorFlow, PyTorch), and data frameworks.</li><li>
Demonstrated success in presales roles: proposal writing, effort estimation, pricing strategies.</li><li>
Excellent communication, presentation, and stakeholder management skills.</li><li>
Understanding of enterprise architecture, data governance, and compliance (GDPR, HIPAA, etc.).</li></ul>
Desired skills:
<ul><li>Experience with GenAI/LLM use cases and frameworks (LangChain, RAG pipelines, etc.).</li><li>
Familiarity with business domains like BFSI, Healthcare, Manufacturing, or Retail.</li><li>
Prior experience working with consulting firms or system integrators is a strong plus.</li><li>
Certifications in AI/ML (e.g., AWS Certified Machine Learning Specialty, Microsoft AI Engineer) are desirable.</li></ul>
Experience:
<div>
8+ years of IT experience with at least 3&ndash;5 years in designing and architecting AI/ML solutions.</div>
Benefits:
<ul><li>Collaborative working environment &ndash; We stand shoulder to shoulder with our clients and our peers, developing solutions that create a sustainable today and tomorrow.</li><li>
Continuous learning - Our Learning &amp; Leadership Development team has established a world-class learning ecosystem that enables you to acquire and develop the right skills by delivering a suite of accredited training courses.</li><li>
Global organisation - We provide solutions to leading brands from various sectors, giving you the opportunity to work with top-tier companies providing impactful solutions to our customers&rsquo; customers.</li></ul></div>

AI Architect

malomatia

<div>
 
 Job Description
 
 
 
 To define technical approach to AI agents, orchestration frameworks, and responsible AI practices while working closely with engineering teams, product managers, and business stakeholders to bring cutting-edge AI capabilities to production.
 
 
 
 Responsibilities
 
 
 
 Lead AI solutions design and implementation
 
 
 <ul>
 <li>
 Serve as the primary technical advisor on generative AI initiatives
 </li>
 <li>
 Lead proof-of-concept development and architectural decision records
 </li>
 <li>
 Mentor engineering teams on agentic AI patterns and best practices
 </li>
 <li>
 Evaluate emerging technologies and maintain technical roadmaps
 </li>
 <li>
 Design and architect AI agent systems and multi-agent workflows for enterprise use cases
 </li>
 <li>
 Evaluate and implement agent frameworks including LangGraph, Microsoft Agent Framework, OpenAI Agents SDK, Google Agent-to-Agent (A2A), and emerging standard
 </li>
 <li>
 Architect tool-use patterns, function calling, MCP, and agent-to-agent communication protocols
 </li>
 <li>
 Design for agent observability, debugging, and human-in-the-loop workflows
 </li>
 <li>
 Design retrieval-augmented generation architectures and architect vector database solutions, embedding strategies, implement chunking strategies, hybrid search, and re- ranking approaches for optimal retrieval performance
 </li>
 <li>
 Design knowledge graphs and structured data integration with generative AI systems
 </li>
 <li>
 Lead architecture decisions across cloud AI platforms including Azure AI Foundry, Google Vertex AI, OpenAI APIs, and open-source Gen AI models
 </li>
 <li>
 Design prompt management, versioning, and optimization pipelines
 </li>
 <li>
 Architect for multi-model strategies, model routing, and fallback patterns
 </li>
 <li>
 Establish patterns for cost optimization, latency management, and scaling LLM workloads
 </li>
 <li>
 Define comprehensive evaluation frameworks for LLM applications and agent systems
 </li>
 <li>
 Implement automated evaluation pipelines using frameworks such as RAGAS, DeepEval, and custom evaluation harnesses
 </li>
 <li>
 Establish benchmarks for response quality, factual accuracy, task completion, and user satisfaction
 </li>
 <li>
 Champion responsible AI practices including safety, fairness, transparency, and privacy
 </li>
 <li>
 Implement guardrails, content filtering, and output validation systems
 </li>
 <li>
 Design for prompt injection prevention, data leakage protection, and secure agent execution
 </li>
 <li>
 Ensure compliance with emerging AI regulations and industry standards
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Engineering, or related field; Master's preferred. Arabic Speaker.
 </li>
 <li>
 8+ years of experience in software engineering or architecture roles
 </li>
 <li>
 3+ years of hands-on experience building LLM-powered applications in production
 </li>
 <li>
 Deep expertise in AI agent architectures, orchestration patterns, and workflow design
 </li>
 <li>
 Strong experience with at least two of the following: LangChain/LangGraph, Microsoft Semantic Kernel/Agent Framework, OpenAI Agents SDK, Google Vertex AI Agent Builder
 </li>
 <li>
 Proven experience designing and implementing Advanced RAG Systems and Agentic AI
 </li>
 <li>
 Proficiency in Python and experience with async programming patterns
 </li>
 <li>
 Hands-on experience with cloud AI platforms (Azure AI Foundry or Google Vertex AI)
 </li>
 <li>
 Strong understanding of Gen AI models&rsquo; fundamentals including prompting, fine-tuning, context windows, and token economics
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience implementing Model Context Protocol (MCP), Google Agent-to-Agent (A2A) protocol, and multi-agent communication patterns
 </li>
 <li>
 Experience building AI Evals pipelines and AI quality assurance systems
 </li>
 <li>
 Knowledge of advanced RAG techniques: query decomposition, multi-hop reasoning, GraphRAG
 </li>
 <li>
 Experience with AI observability tools
 </li>
 <li>
 Background in AI safety, red-teaming, or responsible AI implementation.
 
 
 </li>
 </ul>
 Skills &amp; Competencies
 
 
 <ul>
 <li>
 Systems thinking with ability to design for complexity and emergence in agentic systems
 </li>
 <li>
 Strong communication skills to convey AI concepts to diverse audiences
 </li>
 <li>
 Pragmatic approach balancing innovation with production readiness
 </li>
 <li>
 Ability to rapidly learn evolving AI technologies
 </li>
 <li>
 Commitment to ethical AI development and user safety
 </li>
 <li>
 Collaborative mindset with ability to influence across organizational boundaries
 
 
 </li>
 </ul>
 
 About Malomatia
 
 
 
 
 ABOUT US
 
 
 
 malomatia is a leading Qatar-based IT services and solutions provider, bringing together top Qatari and international talent to deliver innovative, end-to-end technology solutions that empower clients to achieve their strategic goals.
 
 
 
 Our mission
 
 
 
 Empowering Qatar&rsquo;s businesses and governments to leap into the digital future with agile, knowledge-driven solutions.
 
 
 
 Our vision
 
 
 
 To become Qatar&rsquo;s trusted knowledge partner in digital transformation, disrupting industries, shaping the future, and building a world-class tech ecosystem.
 
 
 
 Driving change that makes a real impact
 
 
 
 Since 2008, malomatia has been driving Qatar&rsquo;s digital transformation through innovative, ISO-certified IT solutions. With expertise across key public and private sectors, we empower the nation&rsquo;s vision with advanced services in cloud, cybersecurity, AI, and contact center excellence, elevating the role of technology in shaping Qatar&rsquo;s sustainable future.
 
 
 
 About The Team
 
 
 
 Established in 2008, malomatia is a Qatari leader in IT services and digital transformation. We serve key sectors including Government, Healthcare, Education, Customs, and Transportation, delivering impactful solutions that support national development goals. Powered by a diverse team of skilled Qatari and international IT professionals, we deliver innovative, high-value digital solutions tailored to the unique needs of our clients.
 
 
 Our mission is to inspire customers to thrive through digital excellence, and we envision becoming the trusted partner of choice in building a smarter society through technology and talent. We are driven by core values that define our culture and approach: ownership, integrity, empathy, teamwork, transparency, agility, excellence, trust, and innovation.
 
 
 Join us in shaping the future of technology in Qatar
</div>

Senior Consultant - AI Solution Architect

NVIDIA

<div>We are looking for a Senior Solutions Architect to help leading Enterprise ISVs design, build, and deploy secure agentic AI systems on NVIDIA&rsquo;s accelerated computing platform.
In this role, we will partner with strategic software companies across cybersecurity, AI safety, infrastructure protection, and confidential computing. Together, we will help them build trustworthy AI products that meet enterprise expectations for security, privacy, safety, reliability, and performance.
This work includes multi-agent orchestration, guardrails, agent runtime security, RAG, tool use, model customization, policy enforcement, OpenShell-like execution environments, and confidential AI deployments on protected infrastructure.
What you'll be doing:<ul><li>
Lead strategic agentic AI partner engagements from discovery and architecture through PoC, production readiness, rollout, and scale.</li><li>
Build enterprise-grade agentic AI systems with multi-agent workflows, tool-using agents, RAG, planning, memory, evaluation, guardrails, policy enforcement, and failure containment.</li><li>
Partner with security ISVs to integrate NVIDIA models into detection and response products, including threat triage, investigation agents, remediation workflows, natural-language-to-query, analyst automation, PII handling, and content safety.</li><li>
Architect secure and confidential AI deployments using NVIDIA Confidential Computing, GPU attestation, KMS integration, protected infrastructure, air-gapped patterns, and partner key-management workflows.</li><li>
Create PoCs, benchmarks, reference architectures, reusable blueprints, field guidance, and product feedback that help NVIDIA and our partners move secure AI systems into production.</li></ul>
What we need to see:<ul><li>
BS, MS, or PhD in Computer Science, Electrical Engineering, AI/ML, or equivalent experience</li><li>
8+ years in engineering, solutions architecture, applied ML, enterprise software, or technical deployment.</li><li>
Experience leading AI, ML, distributed systems, or enterprise software projects from prototype to production.</li><li>
Hands-on experience building LLM, generative AI, RAG, or agentic AI applications in production or production-like environments.</li><li>
Depth in one or more areas such as AI/LLM security, enterprise cybersecurity, trust and safety, confidential computing, secure AI infrastructure, model customization, post-training, or model evaluation.</li><li>
Strong Python and Linux skills, experience with PyTorch, TensorFlow, or similar frameworks, and working knowledge of risks such as prompt injection, jailbreaks, tool-based data exfiltration, unsafe tool invocation, and model or skill supply-chain risk.</li></ul>
Ways to stand out from the crowd:<ul><li>
Experience with NVIDIA AI software such as NIM, NeMo Framework, NeMo Retriever, NeMo Guardrails, NeMo Agent Toolkit, Dynamo, Nemotron, Nemotron Safety models, Triton, TensorRT-LLM, or NIM Operator.</li><li>
Experience with LLM red-teaming, AI safety evaluation, adversarial testing, prompt-injection defense, policy enforcement, Garak, NeMo Auditor, or release-gating evaluation benchmarks.</li><li>
Experience with OpenShell, agent harnesses, sandboxed execution, secure tool invocation, agent runtime security, AI/software supply-chain security, model or skill signing, provenance, attestation, VEX, or secure model registries.</li><li>
Experience building post-training pipelines or GPU-accelerated safety and security workflows, including reasoning, tool use, domain adaptation, safety alignment, PII/NER detection, content-safety models, TensorRT optimization, quantization, workshops, architecture reviews, whitepapers, or reference architectures.</li><li>
Experience with confidential computing, including GPU confidential computing, remote attestation, Confidential Containers, enterprise KMS, air-gapped deployments, AMD SEV-SNP, or Intel TDX.</li></ul>
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world&rsquo;s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. This role presents an opportunity to have a wide impact at NVIDIA by improving the factory planning function. Are you creative, hard-working, dedicated, and determined? Do you love a challenge? If so, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.<div><div><div><div><div><div><div>
You will also be eligible for equity and benefits.</div></div></div></div></div></div></div>
Applications for this job will be accepted at least until September 1, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.</div>

Senior Solutions Architect, Agentic AI — Safety and Security

Nagarro

<div>
 
 Job Description
 
 
 
 Must have Skills : Architecture (Strong), Cloud architecture (Strong), Technology Architect - Data Architecture (Strong), Technology Architect - Generative AI,
 
 
 Experience: 12+ Years Role Overview We are seeking a seasoned Enterprise &amp; Solution Architect with strong cross-domain expertise and deep technology capabilities to drive large-scale digital transformation initiatives. The role requires a strategic thinker with hands-on architecture experience across industries such as Telecom, Energy, Public Sector, and BFSI, combined with strong proficiency in modern technology stacks including cloud, web, and advanced Data &amp; AI.
 
 
 Key Responsibilities - Define and drive enterprise architecture strategy aligned with business goals across multiple industry domains (Telco, Energy, Public Sector, BFSI). - Lead end-to-end solution architecture for large, complex transformation programs, ensuring scalability, security, and performance. - Design and govern data-driven architectures, including data platforms, analytics ecosystems, and AI/ML solutions. - Architect and implement solutions leveraging Cloud (OCI/AWS/Azure/GCP), Microservices, APIs, and Modern Web Technologies. - Drive adoption of AI capabilities, including Machine Learning, Generative AI, and emerging Agentic AI frameworks for enterprise use cases. - Establish architecture governance, standards, and best practices across programs and portfolios. - Collaborate with business stakeholders to translate requirements into scalable and future-ready architecture blueprints. - Provide technical leadership across delivery teams, ensuring alignment with architecture vision and quality benchmarks. - Evaluate and recommend technology platforms, tools, and vendors aligned with enterprise strategy. - Lead solutioning for RFPs, proposals, and client engagements, including effort estimation and technical strategy.
 
 
 Key Skills &amp; Competencies Domain Expertise - Strong understanding of at least two or more domains: o Telecom (BSS/OSS, Digital Channels) o Energy &amp; Utilities o Public Sector (eGov, Smart City) o BFSI (Banking, Payments, Insurance) Technology Expertise - Cloud Platforms: AWS, Azure, or GCP (multi-cloud exposure preferred) - Architecture Patterns: Microservices, Event-driven, API-first, Domain-driven design - Web Technologies: Modern front-end and backend frameworks - Integration: APIs, Middleware, ESB, iPaaS Data &amp; AI (Core Focus) - Strong expertise in Data Architecture (Data Lakes, Data Warehouses, Lakehouse) - Hands-on experience with Machine Learning models and lifecycle management (MLOps) - Experience in Generative AI (LLMs, prompt engineering, RAG architectures) - Exposure to Agentic AI systems (autonomous agents, orchestration frameworks) - Knowledge of data governance, security, and privacy frameworks
 
 
 Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, or related field - Architecture certifications (TOGAF, Cloud Architect certifications) preferred
 
 
 Leadership &amp; Behavioral Skills - Strong stakeholder management and executive communication skills - Ability to operate at both strategic and hands-on levels - Proven experience in leading distributed and cross-functional teams - Strong problem-solving and decision-making capabilities
</div>

ENTERPRISE ARCHITECT

Optum

<div>Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. 
As a Principal Data Scientist (SG29) within Optum Rx, you will serve as a senior individual contributor, technical architect, and hands-on leader responsible for designing, building, and productionizing advanced AI solutions across Generative AI, Agentic AI, and Classical AI/ML domains. 
You will partner closely with business leaders, product teams, engineering teams, and platform organizations to solve complex healthcare and pharmacy benefit management challenges using cutting-edge AI technologies. This role requires deep expertise in machine learning, large language models (LLMs), agentic systems, and data science, combined with strong architecture and delivery leadership capabilities. 
The ideal candidate brings a proven track record of translating business challenges into scalable, secure, compliant, and production-ready AI solutions that deliver measurable business impact across pharmacy operations, clinical programs, member engagement, provider enablement, cost optimization, and healthcare outcomes. 
Primary Responsibilities:<ul><li>
AI Strategy, Architecture &amp; Technical Leadership<ul><li>
Lead architecture, design, and implementation of enterprise-scale AI solutions across Generative AI, Agentic AI, machine learning, and advanced analytics domains</li><li>
Define technical vision, architecture standards, reusable frameworks, and best practices for AI-driven products and platforms within Optum Rx</li><li>
Serve as the technical authority for AI solution design, balancing business objectives with scalability, reliability, security, governance, and cost considerations</li><li>
Establish reference architectures, design patterns, reusable components, and deployment frameworks to accelerate AI adoption across teams</li><li>
Drive technology evaluations, proof-of-concepts, and innovation initiatives leveraging emerging AI technologies and frameworks</li></ul></li><li>
Generative AI &amp; Agentic AI Development<ul><li>
Design, build, and productionize Agentic AI systems capable of multi-step planning, reasoning, tool utilization, validation, and autonomous workflow execution within defined governance guardrails</li><li>
Develop enterprise GenAI solutions leveraging approved foundation models, including Claude, OpenAI GPT/Codex, and equivalent enterprise LLM platforms</li><li>
Build intelligent assistants and copilots for:<ul><li>
Data exploration and analytics</li><li>
Pharmacy and healthcare operations</li><li>
Engineering productivity</li><li>
Knowledge management</li><li>
Workflow automation</li><li>
Clinical and business decision support</li><li>
Implement advanced Retrieval-Augmented Generation (RAG), Graph RAG, agent orchestration, memory management, tool-calling, and AI workflow patterns</li><li>
Design AI systems that combine LLMs, knowledge graphs, search technologies, business rules, and predictive models to improve accuracy and trustworthiness</li><li>
Establish evaluation frameworks for LLM quality, hallucination reduction, safety, latency, and cost optimization</li></ul></li></ul></li><li>
Classical AI, Machine Learning &amp; Advanced Analytics<ul><li>
Lead development of predictive, prescriptive, and optimization models addressing key healthcare and pharmacy business challenges</li><li>
Apply advanced statistical modeling, machine learning, deep learning, NLP, computer vision, speech technologies, and reinforcement learning where appropriate</li><li>
Build hybrid AI systems that integrate traditional ML models with Generative AI and Agentic AI capabilities</li><li>
Design experimentation frameworks, model evaluation methodologies, and performance optimization strategies</li><li>
Translate complex data assets into actionable insights that drive measurable business improvements</li></ul></li><li>
Healthcare &amp; Pharmacy Solutions<ul><li>
Develop AI-driven solutions utilizing healthcare and pharmacy datasets, including Pharmacy claims, Clinical, Provider, Member, Formulary and utilization data</li><li>
Architect solutions that improve, Medication adherence, Clinical quality outcomes, Member experience, Operational efficiency and Cost management</li><li>
Work within highly regulated healthcare environments while ensuring compliance with privacy, security, and governance requirements</li></ul></li><li>
Platform Engineering &amp; AI Operations<ul><li>
Partner with platform, cloud, data engineering, and product teams to deploy scalable AI/ML systems</li><li>
Lead adoption of MLOps, LLMOps, and AgentOps capabilities, including:</li><li>
Prompt management</li><li>
Model versioning</li><li>
Experiment tracking</li><li>
Automated evaluation</li><li>
Monitoring and observability</li><li>
CI/CD integration</li><li>
Governance controls</li></ul></li><li>
Establish frameworks for:<ul><li>
Drift detection</li><li>
Performance monitoring</li><li>
Incident response</li><li>
Reliability management</li><li>
Cost optimization</li><li>
Build reusable libraries, APIs, accelerators, and shared AI services that support enterprise-wide adoption</li></ul></li><li>
Responsible AI, Security &amp; Governance<ul><li>
Ensure AI solutions comply with healthcare regulatory, privacy, and security requirements</li><li>
Design and implement guardrails including - Prompt protection mechanisms, Tool access controls, Data protection and redaction, PHI-safe workflows, Auditability and traceability</li><li>
Create transparent documentation covering model behavior, risks, limitations, controls, and mitigation strategies</li><li>
Promote responsible AI practices throughout the solution lifecycle</li><li>
Collaboration &amp; Influence</li><li>
Partner with executive leadership, business stakeholders, product organizations, and engineering teams to identify high-value AI opportunities</li><li>
Influence enterprise AI strategy through technical expertise, innovation, and delivery excellence</li><li>
Communicate complex technical concepts, architectural decisions, and analytical outcomes to both technical and non-technical audiences</li><li>
Mentor and guide data scientists, engineers, and AI practitioners through technical leadership and best practices</li><li>
Drive adoption through reusable artifacts, solution accelerators, reference implementations, and technical standards rather than direct people management</li></ul></li><li>
Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so</li></ul>
Required Qualifications:<ul><li>
Bachelor's degree in Computer Science, Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or related discipline</li><li>
14+ years of overall experience in Data Science, Artificial Intelligence, Advanced Analytics, or Machine Learning</li><li>
7+ years of hands-on experience delivering production-grade AI/ML solutions in large enterprise</li><li>
Hands-on experience developing and deploying enterprise AI solutions using modern frameworks including: Scikit-learn, TensorFlow, PyTorch, LangChain, LangGraph, LlamaIndex, Vector Databases</li><li>
Solid experience working with enterprise LLM platforms such as Claude, OpenAI GPT/Codex, and equivalent technologies</li><li>
Experience with cloud-native AI platforms and distributed computing environments</li><li>
Solid proficiency in Python, SQL, and modern software engineering practices</li><li>
Demonstrated expertise across: Machine Learning, Deep Learning, Natural Language Processing, Generative AI, Agentic AI, Large Language Models, Advanced Analytics</li><li>
Proven expertise in Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, evaluation frameworks, and LLM safety mechanisms</li><li>
Demonstrated expertise in MLOps, LLMOps, and AgentOps practices</li><li>
Proven ability to architect, design, and deliver scalable AI solutions from ideation through production operations</li><li>
Proven excellent communication, stakeholder management, and technical leadership skills</li></ul> 
Preferred Qualification:<ul><li>
Master's degree or equivalent advanced experience</li></ul> 
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.</div>

Principal Data Scientist

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