manager engineering ai data ai data ai architect

Deloitte

<div>
 
 EAI&amp;D &ndash; AI &amp; Data &ndash; AI Architect Manager
 
 
 
 
 About Deloitte
 
 : When you work for us, you commit to a career at one of the largest and most prestigious professional services firms in the world. We have received numerous awards over the last few years, including Best Employer in the Middle East, and Best Consulting Firm, and the Middle East Training &amp; Development Excellence Award.
 
 
 
 Our Purpose
 
 
 
 Deloitte makes an impact that matters. Every day we challenge ourselves to do what matters most&mdash;for clients, for our people, and for society. We serve clients distinctively, bringing innovative insights, solving complex challenges and unlocking sustainable growth. We inspire our talented professionals to deliver outstanding value to clients, providing an exceptional career experience and an inclusive and collaborative culture. We contribute to society, building confidence and trust in the markets, upholding the integrity of organizations and supporting our communities.
 
 
 Our shared values guide the way we behave to make a positive, enduring impact:
 
 
 We are seeking a highly experienced
 
 AI Architect at Manager level
 
 to lead the design, development, and delivery of cutting-edge AI solutions for our clients. The role combines deep technical expertise in artificial intelligence with the ability to shape strategic engagements, advise senior stakeholders, and lead multidisciplinary teams. This is a client-facing leadership position where you will architect enterprise-grade AI solutions that drive measurable business impact.
 
 
 
 Key Responsibilities
 
 
 
 
 Strategy &amp; Advisory
 
 
 
 <ul>
 <li>
 Act as a trusted advisor on emerging AI trends (generative AI, agentic AI, decision intelligence, industrial AI, digital twins, etc.) and their enterprise applications.
 
 
 </li>
 </ul>
 
 Architecture &amp; Solution Design
 
 
 
 <ul>
 <li>
 Define enterprise-scale AI architectures, including LLM-based solutions, MLOps, agent orchestration, data pipelines, and integration with existing enterprise platforms (SAP, Oracle, Salesforce, ServiceNow).
 </li>
 <li>
 Establish best practices in trust, risk, governance, and compliance, ensuring adherence to regulatory frameworks (e.g., GDPR, PDPL, NDMO).
 </li>
 <li>
 Provide architectural leadership across AI infrastructure (cloud platforms such as GCP, AWS, Azure), model deployment frameworks, and edge/on-device AI where relevant.
 
 
 </li>
 </ul>
 
 Delivery &amp; Execution
 
 
 
 <ul>
 <li>
 Lead end-to-end delivery of complex AI programs, from PoC through scaling into production.
 </li>
 <li>
 Collaborate with engineering, data science, and consulting teams to ensure solutions are scalable, secure, and high-performing.
 </li>
 <li>
 Drive the industrialization of AI assets into reusable accelerators and IP for the firm.
 
 
 </li>
 </ul>
 
 Leadership &amp; Practice Building
 
 
 
 <ul>
 <li>
 Mentor and develop AI architects, engineers, and consultants within the firm.
 </li>
 <li>
 Contribute to the growth of the AI consulting practice through go-to-market offerings, client proposals, and thought leadership.
 </li>
 <li>
 Represent the firm at industry forums, conferences, and client workshops as a thought leader in AI architecture.
 
 
 </li>
 </ul>
 
 Qualifications &amp; Experience
 
 
 
 <ul>
 <li>
 8-10 years of professional experience with at least 4+ years in AI/ML architecture roles.
 </li>
 <li>
 Proven experience in consulting or advisory, ideally within Big 4, top-tier consulting, or a global systems integrator.
 </li>
 <li>
 Strong technical foundation in:
 </li>
 <ul>
 <li>
 Large Language Models (LLMs), generative AI, and agent-based systems
 </li>
 <li>
 MLOps, data engineering, cloud-native AI solutions (GCP, Azure, AWS)
 </li>
 <li>
 Enterprise application ecosystems (ERP, CRM, HRM platforms)
 </li>
 <li>
 AI security, governance, and compliance frameworks
 </li>
 </ul>
 <li>
 Track record of leading large-scale AI programs and cross-functional teams.
 </li>
 <li>
 Strong business acumen with ability to translate complex AI concepts into executive-level narratives and measurable value.
 </li>
 <li>
 Advanced degree in Computer Science, Computer Engineering, AI or related field preferred.
 </li>
 <li>
 Willingness to travel across GCC region (50-75% of time)
 
 </li>
 </ul>
 
 Additional Preferred Qualifications
 
 
 
 <ul>
 <li>
 Arabic language is a plus.
 </li>
 <li>
 Professional Certifications in the field is a plus.
 </li>
 <li>
 Publications or articles on Artificial Intelligence topics is a plus.
 
 
 </li>
 </ul>
 
 Key Competencies
 
 
 
 <ul>
 <li>
 Strategic Thinking &ndash; Ability to shape enterprise AI transformation journeys.
 </li>
 <li>
 Technical Leadership &ndash; Expertise in designing and governing scalable AI architectures.
 </li>
 <li>
 Client Engagement &ndash; Strong consulting skills, executive presence, and storytelling ability.
 </li>
 <li>
 Innovation Mindset &ndash; Passion for exploring emerging AI paradigms and turning them into business value.
 </li>
 <li>
 People Leadership &ndash; Proven ability to mentor, inspire, and build high-performing teams.
 
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 <ul>
 <li>
 Opportunity to lead AI architecture for some of the region&rsquo;s most ambitious transformation programs.
 </li>
 <li>
 A platform to shape the future of AI consulting and build new IP and accelerators.
 </li>
 <li>
 Career growth in a dynamic, fast-scaling practice with global exposure.
 </li>
 <li>
 Excellent communication and interpersonal skills to foster effective collaboration with team members and stakeholders.
 </li>
 <li>
 Proven problem-solving and critical-thinking abilities, with a focus on driving innovative solutions.
 </li>
 <li>
 Strong business acumen, identifying opportunities where data science can drive business value and growth.
 </li>
 </ul>
</div>

Manager | Engineering AI & Data | AI & Data | AI Architect

<div>About the role:
PwC is rapidly expanding its market leading Responsible AI (RAI) practice in the UK to meet fast growing client demand across all sectors. As a Senior Manager and Responsible AI Solution Architect, you will shape and deliver PwC&rsquo;s Responsible AI, Ethics, Security and Trust agenda. You will lead the architecture and delivery of trusted AI solutions across GenAI and agentic platforms, working at the intersection of engineering, cyber, data, model risk and regulatory compliance. You will help clients move from principles to production by designing secure, governed and observable AI systems. This role offers the opportunity to influence how some of the UK&rsquo;s largest organisations adopt AI responsibly through technical design leadership, assurance-by-design, and scalable governance patterns. 
What your days will look like:
As a Senior Manager and Responsible AI Solution Architect, you will lead the design and delivery of trusted, secure and compliant AI systems across GenAI and emerging agentic platforms. Working across engineering, cyber, data governance and model risk, you will translate Responsible AI principles and regulatory requirements into production ready architectures. This is a hands on technical leadership role shaping how major organisations build, validate and scale AI safely.<ul><li>Architect end-to-end AI / GenAI / agentic solutions (from data and identity through model integration, orchestration, deployment, monitoring and incident response), embedding PwC&rsquo;s &ldquo;Trust by Design&rdquo; architecture patterns to ensure systems are secure, governed, transparent and resilient.</li><li>Develop and mature PwC&rsquo;s &ldquo;Trust by Design&rdquo; reference architectures and patterns for GenAI and agentic AI, embedding:</li><li>safety and policy controls (guardrails, content safety, prompt-hardening),</li><li>transparency and auditability (logging, traceability, lineage),</li><li>privacy and security controls (data minimisation, encryption, key management),</li><li>and human-in-the-loop and escalation mechanisms.</li><li>Translate regulatory, policy, privacy and ethical requirements into concrete technical controls embedded across:</li><li>SDLC and secure-by-design practices,</li><li>data lifecycle and data governance,</li><li>model lifecycle (training, fine-tuning, evaluation, release, monitoring).</li><li>Partner with cyber and resilience specialists to advance AI threat modelling, prompt injection and data exfiltration mitigations, adversarial testing, and model assurance approaches.</li><li>Define and lead AI assurance strategies across testing, validation, monitoring and control effectiveness across classical ML and GenAI.</li><li>Oversee development of test plans and evaluation frameworks including:</li><li>functional performance testing (accuracy/task success),</li><li>safety testing (toxicity, bias, harmful capability),</li><li>robustness testing (adversarial prompts, jailbreak attempts),</li><li>privacy and leakage testing,</li><li>explainability and transparency checks,</li><li>and post-deployment monitoring (drift, incidents, regressions).</li><li>Shape approaches to model validation and independent assurance, including documentation, governance evidence packs, and audit-ready artefacts.</li><li>Act as technical delivery lead / solution architect on flagship engagements, owning architecture decisions, quality, and delivery outcomes.</li><li>Lead multidisciplinary teams across RAI, engineering, cyber, data governance and risk, bringing structure, pace and clarity to complex delivery.</li><li>Codify delivery experience into reusable assets (frameworks, playbooks, accelerators, reference architectures) to scale PwC&rsquo;s methodology and differentiation.</li><li>Contribute to the UK Responsible AI go-to-market strategy, shaping priority offerings, target sectors, alliance motions and client propositions.</li><li>Lead and contribute to technical thought leadership on GenAI, agentic systems, LLM assurance, AI security and governance, staying at the frontier of emerging techniques.</li><li>Mentor and upskill practitioners through internal capability building, training and coaching.</li><li>Build, lead and inspire diverse teams, fostering a culture of ethical innovation, engineering excellence and continuous learning.</li><li>Collaborate with global PwC teams to scale Responsible AI capabilities across the network and share repeatable assets.</li></ul>
This role is for you if you have:<div><ul><li> 
Deep expertise in Responsible AI principles and operating models, including design or assessment of governance/control frameworks aligned to recognised standards (e.g., NIST AI RMF, ISO/IEC 42001).</li><li>Strong understanding of UK/EU AI regulatory landscape (including EU AI Act), data protection, model risk concepts, and AI ethics.</li><li>Proven experience as a solution architect / technical architect designing and implementing enterprise-grade AI systems.</li><li>Strong understanding of GenAI architectures (RAG, tool use, function calling, agents, orchestration patterns), including failure modes and risk controls.</li><li>Hands-on or architecture-level experience with cloud AI platforms and services, ideally across Azure (e.g., Azure AI / Azure OpenAI, Prompt Flow, AML, Purview, Sentinel), AWS (e.g., Bedrock, SageMaker, IAM/KMS, CloudWatch), and other common data platforms, API management, and identity/access patterns.</li><li>Familiarity with AI enabling technologies and ecosystems: vector databases, embedding pipelines, feature stores, model registries, prompt/trace observability, CI/CD for ML/LLM systems.</li><li>Demonstrated ability to design and lead testing and validation approaches for AI systems, including GenAI safety testing, adversarial testing/red teaming, monitoring and incident management.</li><li>Working knowledge of emerging methods such as fine-tuning (e.g. parameter-efficient approaches), evaluation harnesses, and measurement of risk/quality.</li><li>Experience in consulting or industry, including leadership of complex AI/data/analytics/model risk initiatives.</li><li>Strong stakeholder influence: able to advise executives and risk leaders and translate complex technical issues into business and regulatory implications.</li><li>Commercial acumen: experience shaping proposals, leading workstreams, and supporting large engagements alongside Partners.</li></ul></div>
Desirable to have:<div><ul><li> 
Experience with model governance / MRM platforms, GenAI guardrail tools, and LLMOps / observability tooling (prompt/trace evaluation, scoring, monitoring).</li><li>Experience leading or contributing to AI security programmes (threat modelling, prompt injection mitigation, data leakage prevention, secure deployment).</li><li>External thought leadership (publications, speaking, panels) on Responsible/Trustworthy AI.</li><li>Relevant certifications (e.g., ISO lead implementer/auditor) and/or contributions to standards bodies or industry forums.</li></ul></div>
What success looks like in this role:<div><ul><li> 
You can architect a GenAI/agentic solution end-to-end, explain the trade-offs, and embed Trust by Design controls without slowing delivery to a crawl.</li><li>You&rsquo;re comfortable with both platform realities (Azure/AWS services, identity, security, integration, monitoring) and RAI assurance (evidence, testing, validation, governance).</li><li>You can turn lessons learned into repeatable patterns that scale across PwC and across clients.</li></ul></div> 
What you&rsquo;ll receive from us:
No matter where you may be in your career or personal life, our benefits are designed to add value and support, recognising and rewarding you fairly for your contributions.
We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.
Applications close on the 5 of June 2026</div>

Senior Manager, Responsible AI Solution Architect

Realign

<div>Jersey City, New Jersey 07030 Posted August 31st, 2026</div>
 <div><h5 class="jobSectionHeader">Job Type: Full Time</h5>
<h5 class="jobSectionHeader">Job Category: IT</h5>
<h4 class="jobSectionHeader">Job Description</h4>
<div>Role: Senior Gen AI Architect
 
Location: New York City / New Jersey City
</div><div>Hybrid</div>
<div>FTE</div><div> 
</div><div>Job Description</div>
<div>We are looking for a Senior Gen AI Architect with strong expertise in Data Engineering, Analytics, Generative AI, and Agentic AI workflows. The candidate will design and build scalable AI-driven solutions that leverage enterprise data, LLMs, RAG, and agent-based architectures. 
 
 
</div><div>Key Responsibilities:</div>
<ul><li> Design and develop Gen AI and Agentic AI applications using Python and modern AI frameworks.</li></ul>
<ul><li> Build scalable data pipelines, data processing, and analytics solutions.</li></ul>
<ul><li> Develop LLM/RAG-based applications integrating enterprise data sources.</li></ul>
<ul><li> Design and implement agentic workflows, AI agents, orchestration, and tool integrations.</li></ul>
<ul><li> Work with structured and unstructured data to support AI and analytics use cases.</li></ul>
<ul><li> Integrate LLMs with APIs, databases, knowledge sources, and enterprise platforms.</li></ul>
<ul><li> Implement evaluation, monitoring, security, and governance for Gen AI solutions.</li></ul>
<ul><li> Collaborate with Data Engineers, Data Scientists, Architects, and business stakeholders.</li></ul>
<ul><li> Drive solutions from POC/prototype through production deployment. 
</li></ul> 
<div>Must-Have Skills</div>
<ul><li> 15+ years of software/data engineering experience</li></ul>
<ul><li> Strong Python</li></ul>
<ul><li> Generative AI / LLM / RAG</li></ul>
<ul><li> Agentic AI / AI Agents / Agent Orchestration</li></ul>
<ul><li> Strong Data Engineering &amp; Analytics</li></ul>
<ul><li> SQL and modern data platforms</li></ul>
<ul><li> Experience with APIs, microservices, and cloud platforms</li></ul>
<ul><li> Experience with LLM frameworks such as Lang Chain, Lang Graph, or similar</li></ul>
<ul><li> Strong understanding of AI architecture, data architecture, and enterprise integration</li></ul>
<ul><li> Excellent communication and stakeholder management skills</li></ul><div> 
</div><h5 class="jobSectionHeader">Required Skills</h5>
Performance Architect</div>

Senior Gen AI Architect-2

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

Accenture in India

<div>
 
 Project Role :
 
 Large Language Model Architect
 
 
 
 Project Role Description :
 
 Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
 
 
 
 Must have skills :
 
 Large Language Models (LLMs)
 
 
 
 Good to have skills :
 
 Snowflake Data Warehouse
 
 
 
 Minimum 5 Year(s) Of Experience Is Required
 
 
 
 
 Educational Qualification :
 
 15 years full time education
 
 
 
 Role Summary / Description
 
 
 
 AI Powered Tech Talent
 
 
 Engineer role in AI LLM Technology Architecture. Hands-on engineering role focused on designing, building, integrating, testing and operationalizing enterprise-grade LLM, GenAI and agentic AI components across active client engagements.
 
 
 Own platform-specific engineering on Snowflake, translating high-level architecture into working, production-quality components for LLM-driven applications, RAG pipelines, multi-agent workflows and AI platform integrations.
 
 
 Bring practical industry experience in banking, insurance, retail, healthcare, travel, logistics or telecom to identify domain data, process constraints, controls and adoption risks while designing GenAI solutions that are safe, scalable and relevant.
 
 
 Operate as a hands-on technical or engineering lead, contributing code, design decisions, reusable patterns and engineering documentation.
 
 
 Key Responsibilities
 
 
 Design and build LLM application components including prompts, tools, agents, orchestration flows, memory/context handling, retrieval pipelines and evaluation harnesses.
 
 
 Develop Cortex-powered LLM applications and agents inside Snowflake security perimeter build RAG and document intelligence using Cortex Search and Cortex AI Functions integrate Streamlit/Snowpark applications apply RBAC, masking, lineage and monitoring for regulated enterprise use cases.
 
 
 Implement data ingestion, parsing, chunking, enrichment, embeddings, vector search and retrieval workflows for structured and unstructured enterprise content.
 
 
 Engineer safety and control components including PII detection/redaction, prompt-injection defenses, content filters, guardrails, authentication, authorization, lineage and audit logging.
 
 
 Collaborate with architects, data engineers, product owners and security stakeholders to convert solution designs into tested, observable and maintainable software components.
 
 
 Maintain technical artifacts such as component designs, integration specifications, deployment runbooks, evaluation results and reusable engineering patterns.
 
 
 
 Required Qualifications
 
 
 
 Bachelor s degree in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology or a related engineering discipline.
 
 
 Typically 5+ years of software/data/AI engineering experience, including 2+ years in cloud-native engineering and 1+ year in GenAI, LLM, NLP or agentic AI delivery.
 
 
 Typically 7+ years of software/data/AI engineering experience, including 3+ years in cloud-native architecture/engineering and 1&ndash;2+ years in GenAI, LLM, NLP or agentic AI delivery.
 
 
 Hands-on coding experience in Python and strong understanding of APIs, distributed systems, CI/CD, testing, observability and secure SDLC practices.
 
 
 Experience delivering AI/ML or data products in at least one industry domain such as banking, insurance, retail, healthcare, travel, logistics or telecom.
 
 
 
 Required Skills/ Experience
 
 
 
 Hands-on experience with Snowflake Cortex AI, Cortex Agents, Cortex Search, Cortex Analyst, Cortex AI Functions/LLM Functions, Snowpark, Streamlit in Snowflake, Dynamic Tables, Tasks, Streams, Snowflake ML, RBAC, masking policies and observability.
 
 
 Strong understanding of LLM application architecture patterns including RAG, function/tool calling, agent orchestration, model invocation, prompt engineering, embeddings, vector databases and evaluation metrics.
 
 
 Ability to implement traditional ML and GenAI components across ingestion, feature/data preparation, model integration, deployment, monitoring and continuous improvement.
 
 
 Practical knowledge of security, privacy, governance, performance, scalability, reliability and cost controls for production AI systems.
 
 
 Experience with Git-based development, automated testing, CI/CD pipelines, infrastructure-as-code and agile delivery in client-facing environments.
 
 
 Good to Have Skills
 
 
 SnowPro Advanced Architect/Data Engineer or Snowflake ML exposure experience with Snowpark Python, Streamlit, semantic models, dbt, Native Apps, Snowflake governance, data sharing and cost/performance tuning.
 
 
 Exposure to open-source frameworks such as LangChain, LangGraph, LlamaIndex, Haystack, MLflow, FastAPI, Docker and Kubernetes.
 
 
 Experience with Responsible AI, model risk management, synthetic data generation, human-in-the-loop review, A/B testing and GenAI cost optimization.
</div>

Large Language Model Architect

Discovered MENA

<div>
 
 AI Software Architect (AI, Python, DevOps)
 
 
 
 Salary:
 
 40k/45k AED p/month Tax Free
 
 
 
 Location:
 
 Dubai Media City (Onsite)
 
 
 
 Benefits:
 
 Medical insurance, flight allowance, discretionary bonus, birthday gift after one year
 
 
 Discover the opportunity
 
 
 
 
 
 We are seeking a
 
 AI Software Architect
 
 to join a unique tech venture. The company focuses on cutting edge applications centered around security, data privacy, and AI.
 
 
 
 
 
 This role offers exceptional long term stability alongside the fast paced innovation of an agile startup environment. You will work alongside a lean tech team, reporting directly to the Tech Product Manager while taking ownership of core software architecture, AI architecture, and hands on development.
 
 
 
 
 
 Discover the role
 
 
 
 
 
 As a Senior AI Software Architect, you will balance technical strategy with active development in a roughly equal split. You will take end to end architectural ownership of user centric applications, AI solutions, and cloud infrastructure supporting a modular platform.
 
 
 
 
 
 You will lead the integration of
 
 LLMs, RAG pipelines, and agentic AI systems
 
 into reliable, scalable production applications while ensuring cloud native services remain secure, compliant, and observable. This is an individual contributor position designed for a skilled builder who thrives in a fast moving environment.
 
 
 
 
 
 Discover the responsibilities
 
 
 
 
 <ul>
 <li>
 Take complete ownership of software, AI, and platform architecture from initial design through production deployment
 </li>
 <li>
 Spend half your time writing hands on code, specifically building and integrating AI solutions using
 
 Python, LLMs, RAG, and agentic AI
 
 </li>
 <li>
 Design, deploy, and manage multi tenant microservices infrastructure across AWS cloud environments and
 
 Amazon EKS/Kubernetes clusters
 
 </li>
 <li>
 Build and integrate production grade LLM applications, including RAG pipelines, AI agents, and model integrations
 </li>
 <li>
 Embed zero trust networking, privacy by design, and strict security controls across platforms
 </li>
 <li>
 Build and optimize continuous deployment pipelines, automated testing, infrastructure as code, and full stack observability layers
 </li>
 <li>
 Work extensively with
 
 DevOps and MLOps tooling
 
 , including Terraform, Kubernetes, EKS, CI/CD, and cloud native deployment practices
 </li>
 <li>
 Work on production grade software and AI products built directly for external commercial users
 </li>
 <li>
 Identify and resolve system performance bottlenecks, technical debt, and scalability limitations
 </li>
 </ul>
 
 
 
 
 Discover the requirements
 
 
 
 
 <ul>
 <li>
 Minimum 5 to 7 years of relevant experience in software architecture and hands on engineering
 </li>
 <li>
 Strong hands on development skills in
 
 Python
 
 , with proven experience building and integrating AI solutions
 </li>
 <li>
 Proven commercial experience working with
 
 LLMs, RAG, AI agents, or agentic AI architectures
 
 </li>
 <li>
 Proven experience building commercial SaaS products sold directly to customers
 </li>
 <li>
 Deep technical knowledge of
 
 AWS and Kubernetes
 
 , with hands on experience using
 
 Amazon EKS
 
 </li>
 <li>
 Solid grasp of
 
 DevOps and MLOps practices, Terraform/infrastructure as code, CI/CD, and cloud native tooling
 
 </li>
 <li>
 Strong understanding of zero trust security, data encryption, and data residency standards
 </li>
 <li>
 Experience designing scalable microservices and production grade AI applications
 </li>
 <li>
 Experience in fast paced startup or scaleup environments is strongly preferred
 </li>
 <li>
 Strong understanding of how to take AI/ML solutions from development through to reliable production deployment
 </li>
 </ul>
 
 
 
</div>

AI Software Architect (AI, Python, DevOps)

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

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