agentic ai engineer

Campbell's

<div><p><b>Since 1869, we've connected people through food they love. We&rsquo;re proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell&rsquo;s brand, as well as Cape Cod, Chunky, Goldfish, Kettle Brand, Lance, Late July, Pacific Foods, Pepperidge Farm, Prego, Pace, Rao&rsquo;s Homemade, Snack Factory, Snyder&rsquo;s of Hanover. Swanson, and V8.
</b></p><p></p><p><b>Here, you will make a difference every day. You will be supported to build a rewarding career with opportunities to grow, innovate and inspire. Make history with us.
</b></p><p></p><p><b>Operational Support Data Engineer &ndash; Agentic AI &amp; ML Ops (Co-op)
</b></p><ul><li>We are seeking a motivated and curious Data Engineer &ndash; Agentic AI &amp; ML Ops to join our Enterprise Data &amp; Analytics team. This co-op provides hands-on experience supporting cloud-based data platforms, AI/ML operations, Generative AI, and Agentic AI solutions.
</li></ul><ul><li>You will work with Databricks, Snowflake, Azure, ADLS, ADF, Power BI, Python, PySpark, SQL, LLMs, and modern AI/ML frameworks in an Agile environment.
</li></ul>If you are passionate about data engineering, AI, and automation, we want to hear from you.<br>
<ul><li>
</li></ul><p></p><p><b>Key Responsibilities
</b></p><ul><li>Build Data &amp; AI Pipelines: Develop and support ETL/ELT pipelines and AI/ML workflows.
</li></ul><ul><li>Data Integration &amp; Transformation: Ingest, transform, and orchestrate data using Python, PySpark, and SQL.
</li></ul><ul><li>Develop Agentic AI Solutions: Build and test AI agents and intelligent workflows for automation and data access.
</li></ul><ul><li>LLM &amp; Prompt Engineering: Design and optimize prompts and workflows using LLMs and GenAI frameworks.
</li></ul><ul><li>AI/ML Development &amp; Automation: Build Python-based scripts, APIs, and notebooks on cloud platforms.
</li></ul><ul><li>Support Analytics &amp; AI/ML: Prepare datasets for reporting, ML models, forecasting, and advanced analytics.
</li></ul><ul><li>Monitor &amp; Support Operations: Troubleshoot pipeline failures, performance issues, and data quality gaps.
</li></ul><ul><li>MLOps &amp; CI/CD: Support deployment, testing, and automation for data and AI solutions.
</li></ul><ul><li>Data Modeling &amp; Semantic Layers: Assist with STTM, data modeling, and reporting datasets.
</li></ul><ul><li>Agile Collaboration: Participate in sprint planning, stand-ups, and retrospectives.
</li></ul>Documentation &amp; Automation: Create runbooks, workflows, and technical documentation.<br>
<ul><li>
</li></ul><p></p><p><b>Learning &amp; Development Opportunities
</b></p><ul><li>Hands-on experience with Databricks, Snowflake, Azure, ADLS, ADF, and Power BI.
</li></ul><ul><li>Exposure to MLOps, GenAI, Agentic AI, LLMs, CI/CD, and automation.
</li></ul><ul><li>Experience working with AI agents, prompt engineering, and workflow orchestration.
</li></ul><ul><li>Mentorship from Data, AI/ML, and Platform Engineers.
</li></ul>Experience in Agile/Scrum and DevOps/MLOps environments.<br>
<ul><li>
</li></ul><p></p><p><b>Qualifications
</b></p><ul><li>Pursuing a degree in Computer Science, Data Engineering, Data Science, AI/ML, or related field.
</li></ul><ul><li>Knowledge of SQL, Python/PySpark, ETL/ELT, and APIs.
</li></ul><ul><li>Familiarity with Databricks, Snowflake, Azure, ADLS, ADF, Power BI, or Git is a plus.
</li></ul><ul><li>Exposure to LLMs, GenAI, Agentic AI, MLOps, or CI/CD is beneficial.
</li></ul><ul><li>Experience with Python-based AI/ML projects or notebooks is a plus.
</li></ul><ul><li>Strong analytical and problem-solving skills.
</li></ul><ul><li>Strong communication and teamwork skills.
</li></ul><p></p><p>The Company is committed to providing equal opportunity for employees and qualified applicants in all aspects of the employment relationship, including consideration for employment, without regard to race, color, sex, sexual orientation, gender identity, national origin, citizenship, marital status, protected veteran status, disability, age, religion, or any other classification protected by law.</p></div>

Data Engineer – Agentic AI & ML Ops (Co-op)

Datamatics Global Services Ltd

<div><b>Position Title : AI/ML Engineer &ndash; Agentic AI</b><br>
<b>Experience Required: </b>4&ndash;6 Years (Should be open to Travel)<br>
<b>Employment Type : </b>Full-Time - Riyadh - Onsite<br>
<br>
<b>Job Overview</b><br>
We are seeking a highly skilled AI/ML Engineer with hands-on experience in building intelligent AI systems, machine learning models, and Agentic AI solutions. The ideal candidate will have strong expertise in designing, developing, and deploying AI-powered applications leveraging LLMs, autonomous agents, orchestration frameworks, and modern ML techniques.<br>
The role requires a strong engineering mindset, practical AI implementation experience, and the ability to work across the full AI/ML lifecycle from experimentation to production deployment.<br>
<br>
<b>Key Responsibilities</b><ul><li>
Design, develop, and deploy AI/ML solutions for real-world business use cases.</li><li>
Build and optimize <b>Agentic AI systems</b> using LLMs, autonomous workflows, and multi-agent architectures.</li><li>
Develop machine learning models for prediction, classification, recommendation, NLP, and automation tasks.</li><li>
Work with orchestration frameworks such as LangChain, CrewAI, AutoGen, LangGraph, or similar technologies.</li><li>
Integrate AI agents with APIs, databases, enterprise systems, and third-party tools.</li><li>
Fine-tune, evaluate, and optimize Large Language Models (LLMs).</li><li>
Develop Retrieval-Augmented Generation (RAG) pipelines and vector search implementations.</li><li>
Collaborate with data engineers, software developers, and product teams to deliver scalable AI solutions.</li><li>
Perform prompt engineering, model experimentation, and performance optimization.</li><li>
Ensure AI solutions are production-ready, scalable, secure, and cost-efficient.</li><li>
Monitor model performance, drift, and continuous improvement processes.</li><li>
Stay updated with emerging AI, Generative AI, and Agentic AI trends and technologies.</li></ul><b>
Required Skills &amp; Expertise</b><ul><li>
Strong hands-on experience in <b>Machine Learning, Generative AI, and Agentic AI development</b>.</li><li>
Proficiency in Python and AI/ML development frameworks.</li><li>
Experience with:<ul><li>
LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks</li><li>
OpenAI, Anthropic, Gemini, or open-source LLMs</li><li>
RAG architectures and Vector Databases</li><li>
Prompt Engineering &amp; AI workflow automation</li></ul></li><li>
Solid understanding of:<ul><li>
NLP concepts</li><li>
ML algorithms and model evaluation</li><li>
Deep Learning fundamentals</li><li>
AI model deployment and inference optimization</li></ul></li><li>
Experience with ML libraries/frameworks such as:<ul><li>
PyTorch</li><li>
TensorFlow</li><li>
Scikit-learn</li><li>
Hugging Face Transformers</li></ul></li><li>
Experience with cloud platforms such as Azure, AWS, or GCP is preferred.</li><li>
Familiarity with Docker, APIs, CI/CD, and MLOps practices.</li><li>
Strong problem-solving and analytical skills.</li></ul><b>
Preferred Qualifications</b><ul><li>
Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, or related field.</li><li>
Experience working on enterprise AI automation or AI assistant platforms is highly preferred.</li><li>
Exposure to AI governance, evaluation frameworks, and AI observability tools is a plus.</li></ul><br>
<p>
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AI/ML Engineer – Agentic AI

Etisalat

<div><div><b>AI Development Senior Principal Engineer.Customer and Partner Management</b> <b>-</b> <b>(</b><b>260000ZA</b><b>)</b></div><div><b>
Description</b><div></div><p><b><br>
Job Purpose</b></p><p>
Lead AI model development programs (OCR, multimodal, conversational AI, agentic AI, STT/TTS), define the technical roadmap for model capabilities, guide PoCs to production, and ensure the AI product portfolio delivers measurable business impact.
</p><p><b>
Report To Position Name</b></p><p>
Strategy &amp; Roadmap Define AI/GenAI roadmap aligned with business strategy (conversational experiences, voice automation, knowledge assistants). Evaluate vendor vs open-source LLM options; define hybrid multi-LLM strategies. Product &amp; PoC Leadership Lead productization: turn PoCs into resilient AI services (model lifecycle, monitoring, rollout). Sponsor and validate PoCs for agentic AI, RAG-driven assistants, multimodal features and STT/TTS voice bots. Architecture &amp; Governance Define model architecture standards, security and compliance guardrails, and explainability approaches. Set MLOps standards (training pipelines, model registry, CI/CD for models, drift detection). Team Leadership Manage and grow a high-performing AI engineering team; mentor senior staff and data scientists. Coordinate cross-functional efforts with platforms, product and operations. Stakeholder Engagement Translate business requirements into model specs, ROI assumptions and deployment plans. Present outcomes and technical risk to executive stakeholders.</p><div><br>
</div></div><div><b>
Qualifications</b><div></div><p><b><br>
QUALIFICATIONS_ESSENTIAL</b></p><p>
Master's or PhD in AI/ML strongly preferred</p><p><b><br>
QUALIFICATIONS_DESIRABLE</b></p><p>
Architect enterprise solutions for production scaling, cost/latency trade-offs, model governance.</p><p><b><br>
EXPERIENCE_ESSENTIAL</b></p><p>
4+ years in AI/ML, including leadership delivering commercial AI products.</p><p><b><br>
EXPERIENCE_DESIRABLE</b></p><p>
Expert in generative AI, agentic systems, RAG, embeddings &amp; vector DBs, STT/TTS solutions, production MLOps and ethical AI practices</p><p><b><br>
CERTIFICATIONS_ESSENTIAL</b></p><p>
N/AN</p><div><br>
</div></div><div><b>
Job</b><b>:</b> Senior Principal Engineer</div><div><b>
Organization</b><b>:</b> Etisalat-Misr</div><div><b>
Job Posting</b><b>:</b> 07/Jun/2026, 12:42:16 PM</div></div>

AI Development Senior Principal Engineer.Customer and Partner Management

MANTECH

<div><p>MANTECH seeks a motivated, career, and customer-oriented <b>AI Engineer</b> for a new initiative. This effort supports the rapid design, deployment, operation, and sustainment of enterprise-scale AI, data, and mission platform capabilities across a cloud, edge, and classified operational environment.</p><p>
The <b>AI Engineer</b> supports the development and operationalization of advanced AI and agentic AI systems in production mission environments. You will accelerate operational AI adoption through a modern Hub-and-Spoke architecture, supporting mission applications and enterprise AI governance.</p><p></p><p><b>
Responsibilities include but are not limited to:</b></p><ul><li>
Design, develop, and operationalize full-lifecycle AI/ML operations (MLOps/LLMOps).</li><li>
Implement and deploy Retrieval-Augmented Generation (RAG) architectures in production.</li><li>
Build and maintain scalable AI orchestration frameworks and production-ready AI systems.</li><li>
Manage and optimize Kubernetes-based AI deployments, focusing on GPU inference optimization.</li><li>
Conduct core Python development for AI systems and integrate OpenAI-compatible APIs into mission solutions.</li><li>
Operationalize AI agents using advanced frameworks like LangGraph or Semantic Kernel.</li></ul><p></p><p><b>
Minimum Qualifications:</b></p><ul><li>
Must possess 7 or more years of experience in AI/ML production engineering, development, or related roles. Relevant additional experience will be considered in lieu of degree.</li><li>
Proven proficiency in Python development and experience with AI/ML libraries like TensorFlow or PyTorch.</li><li>
In-depth knowledge of MLOps/LLMOps principles and full machine learning lifecycle management.</li><li>
Experience with Kubernetes-based AI deployments and GPU optimization techniques.</li><li>
Proven experience designing, building, securing or monitoring scalable solutions within the Microsoft Azure ecosystem (e.g., Azure OpenAI, Azure Synapse, Databricks, or Azure Security Center).</li></ul><p></p><p><b>
Preferred Qualifications:</b></p><ul><li>
Bachelor&rsquo;s degree in Computer Science, Engineering or a related field.</li><li>
Experience with LangGraph, Semantic Kernel, and agentic AI systems.</li><li>
Familiarity with Ray, NVIDIA GPU ecosystems, or Vector databases.</li><li>
Advanced degree (Master's or PhD) in a technical field.</li></ul><p></p><p><b>
Clearance Requirements:</b></p><ul><li>
TS/SCI with the ability to obtain and maintain a polygraph</li></ul><p></p><p><b>
Physical Requirements:</b></p><ul><li>
The person in this position must be able to remain in a stationary position 50% of the time.</li><li>
Frequently communicates with co-workers, management, and customers, which may involve delivering presentations.</li><li>
Constantly operates a computer and other office productivity machinery.</li></ul></div><p></p>

AI Engineer

Tata Consultancy Services (TCS)

<div></div><div><div><div><div><p><b>Must-Have Skills</b></p>
<ul><li>Strong AI/ML engineering and software development experience</li>
<li>Expertise in LLMs, Gemini APIs, Vertex AI, and Google Cloud</li>
<li>Experience building agentic AI workflows, copilots, and intelligent agents</li>
<li>Hands-on implementation of RAG systems and vector databases</li>
<li>Strong prompt engineering skills and applied analytics knowledge</li>
<li>Ability to integrate AI solutions with enterprise systems</li>
<li>Experience with middleware, orchestration layers, and API integrations</li>
<li>Knowledge of AI observability, evaluation frameworks, guardrails, and security controls</li>
<li>Strong problem-solving, debugging, and rapid prototyping ability</li>
<li>Excellent communication and stakeholder management skills</li>
<li>Ability to thrive in fast-paced, ambiguous environments with ownership mindset</li>
</ul>
<p><b>Key Responsibilities</b></p>
<ul><li>Develop and deploy AI solutions using Gemini Enterprise, Vertex AI, and Google Cloud</li>
<li>Build prototypes, POCs, and production-grade AI applications rapidly</li>
<li>Design and implement agentic workflows, RAG systems, and AI orchestration pipelines</li>
<li>Integrate LLMs with enterprise platforms and build middleware layers</li>
<li>Create intelligent copilots, multi-modal demos, and automation workflows</li>
<li>Ensure AI systems meet standards for reliability, s ecurity, explainability, and compliance</li>
<li>Implement monitoring, evaluation, and human-in-the-loop frameworks</li>
<li>Work directly with clients to gather requirements and design AI solutions</li>
<li>Lead technical discussions, discovery workshops, and solution demos</li>
<li>Act as a bridge between business stakeholders and engineering teams</li>
</ul></div></div></div><div><div><div><b>Location</b></div>
<div>Milford Center, OH</div>
</div><div><div><b>Job Function</b></div>
<div>TECHNOLOGY</div>
</div><div><div><b>Role</b></div>
<div>Senior Engineer</div>
</div><div><div><b>Job Id</b></div>
<div>416664</div>
</div><div><div><b>Desired Skills</b></div>
<div>Artificial Intelligence</div>
</div><div><div><b>Salary Range</b></div>
<div>$120,000-$160,000 a year</div></div></div></div><div></div>

Forward Deployed Engineer

<div>
 <p>
  CAS uses unparalleled scientific content, specialized technology and unmatched human expertise to help R&amp;D organizations across Commercial, Government and Academic sectors create groundbreaking innovations that benefit the world. As the Scientific Information Solutions Division of the American Chemical Society, CAS manages the largest curated reservoir of scientific knowledge, and for 119 years, has helped innovators mine, assess and apply that information to keep businesses thriving. The CAS team is global, diverse, endlessly curious and strives to make actionable scientific insights accessible to innovators worldwide.
 </p>
 <p>
  CAS is currently seeking a Data Scientist. This position will be located in our headquarters in Columbus, Ohio.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Job Summary
  </strong>
 </p>
 <p>
  This is an individual contributor role on the Data Analytics and Insights (DAI) team, which builds the AI that powers CAS&rsquo;s scientific information products. As a data scientist, you will build the models, agents, and AI-powered features that ship in those products, working alongside data engineers, product managers, and scientific domain experts.
 </p>
 <p>
  This role requires dual-domain expertise: you must be both a capable software engineer and formally trained in a scientific discipline relevant to CAS&rsquo;s customers (chemistry, life sciences, materials science, or a related field). DAI builds AI that is grounded in CAS&rsquo;s scientific content rather than layered on top of it, so the people who build it need to read the science as well as write the code. You will work on features such as the Newton research assistants in SciFinder and BioFinder, the natural-language query agent in IPFinder, predictive models that ship inside products (for example property, toxicity, or biologic developability prediction), and AI-assisted content curation pipelines, using your scientific training to judge whether their outputs are correct and useful to working scientists.
 </p>
 <p>
  Success in this role requires strong programming fundamentals, formal scientific training, a genuine interest in agentic AI, and a collaborative approach to building reliable, production-grade systems. Candidates who bring only software engineering or only scientific training are not a fit for this position.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Job Accountability
  </strong>
 </p>
 <ul>
  <li>
   Develop and deploy agent-based workflows, retrieval-augmented generation (RAG) pipelines, and LLM-powered features within CAS products using Python, LangGraph/LangChain, and related tools.
  </li>
  <li>
   Develop and deploy machine learning models that ship inside CAS products (for example property, toxicity, or biologic developability prediction), using your scientific training to inform feature design and to validate model behavior.
  </li>
  <li>
   Ground agentic and predictive features in CAS&rsquo;s authoritative scientific content, and use your scientific training to judge whether system outputs are accurate, defensible, and useful to researchers.
  </li>
  <li>
   Engineer for production, not for demos: deliver clean, tested, well-documented software with appropriate safeguards such as content safety guardrails, entitlement-based access control, evaluation, and model fallback, following team engineering standards (unit, integration, and end-to-end tests, containerized development, and CI/CD practices).
  </li>
  <li>
   Work with product managers, scientific domain experts, data engineers, and other teams to translate scientific and research requirements into working technical solutions.
  </li>
  <li>
   Contribute to evaluation frameworks for GenAI systems, focusing on accuracy, reliability, scientific correctness, and continuous improvement of agentic features.
  </li>
  <li>
   Build and operate solutions on cloud infrastructure (AWS, Azure, GCP, or similar), supporting the production deployment and ongoing operations of AI systems.
  </li>
  <li>
   Use agentic software development tools such as Claude Code as a core part of the daily workflow to accelerate delivery and maintain quality.
  </li>
  <li>
   Contribute to DAI&rsquo;s innovation and competitive-intelligence work by prototyping emerging AI capabilities and running structured experiments that test where AI can replicate or extend CAS capabilities.
  </li>
  <li>
   Stay current with advances in generative AI and agentic architectures, and share knowledge with the team through demos, documentation, and internal learning sessions.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Required Qualifications
  </strong>
 </p>
 <p>
  This role requires expertise in two domains. Both the scientific and the software engineering qualifications below are required, not alternatives.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Scientific domain
  </strong>
 </p>
 <ul>
  <li>
   Bachelor&rsquo;s degree or higher in a scientific discipline relevant to CAS&rsquo;s customer domains (chemistry, life sciences, materials science, or a closely related field). This scientific training is a gating requirement for the role, not a preference.
  </li>
  <li>
   The ability to read scientific content in your field and reason about it accurately enough to evaluate the outputs of AI systems that serve working scientists (for example, recognizing when a predicted property or a generated answer is wrong).
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Software engineering and AI domain
  </strong>
 </p>
 <ul>
  <li>
   2+ years of professional experience in software engineering, applied machine learning, or data science, with demonstrated delivery of working systems.
  </li>
  <li>
   Strong Python programming skills with solid software engineering fundamentals (version control, testing, code review, documentation).
  </li>
  <li>
   Hands-on experience building applications with large language models, including agentic workflows, RAG, prompt engineering, or similar patterns.
  </li>
  <li>
   Experience with or strong interest in agentic AI frameworks such as LangGraph, LangChain, or equivalent platforms.
  </li>
  <li>
   Proficiency with agentic software development tools (e.g., Claude Code or similar AI-assisted development environments).
  </li>
  <li>
   Experience deploying and operating software in at least one cloud environment (AWS, Azure, or GCP).
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Both domains
  </strong>
 </p>
 <ul>
  <li>
   Strong written and verbal communication skills, with the ability to work effectively in cross-functional teams that include both engineers and scientists.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Desired but Not Required
  </strong>
 </p>
 <ul>
  <li>
   Graduate degree (M.S. or Ph.D.) in a scientific discipline relevant to CAS&rsquo;s customer domains, giving deeper command of the science behind the products.
  </li>
  <li>
   Coursework, a second degree, or equivalent experience in Computer Science, Engineering, or Statistics that complements the scientific training.
  </li>
  <li>
   Experience building and deploying predictive ML models in a scientific or regulated domain.
  </li>
  <li>
   Experience with cloud AI/ML services and model hosting platforms.
  </li>
  <li>
   Familiarity with containerized development workflows and API design.
  </li>
  <li>
   Experience with evaluation frameworks for AI/ML systems, including accuracy, reliability, and cost optimization.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  CAS offers a competitive salary and comprehensive benefits package, including a generous vacation plan, medical, dental, vision insurance plans, and employee savings and retirement plans. Candidates for this position must be authorized to work in the United States and not require work authorization sponsorship by our company for this position now or in the future. EEO/Disabled/Veteran
 </p>
 <p>
 </p>
</div>


Data Scientist

MVP Application and game design L.L.C

<p>We are looking for an <b>Agentic AI Developer</b> who can design, build, and optimize advanced AI systems that go beyond simple chatbot or basic RAG implementations. The ideal candidate should have hands-on experience creating <b>multi-agent workflows, tool-using AI agents, retrieval systems, reasoning pipelines, orchestration layers, and production-ready AI architectures</b>.</p><p>This role requires someone who understands how to build complex AI systems where multiple components work together, including LLMs, vector databases, APIs, memory, tools, workflows, permissions, guardrails, and backend services. The candidate should be able to think architecturally, break down business problems into AI workflows, and design systems that are scalable, secure, reliable, and suitable for enterprise or government environments.</p><p>The candidate should also have basic to intermediate knowledge of <b>Node.js</b>, enough to connect AI services with backend APIs, build lightweight services, integrate third-party tools, and support implementation with the engineering team.</p><p><b>Technical Requirements</b></p><p>The candidate should have hands-on experience with:</p><ul><li><b>Agentic AI frameworks</b> such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or custom orchestration layers</li><li><b>Agent loops</b>, planning/execution flows, task decomposition, reflection, validation, and human-in-the-loop workflows</li><li><b>Tool calling / function calling</b>, structured outputs, JSON schemas, API execution, and tool safety controls</li><li><b>Stateful AI workflows</b>, including state machines, graph-based orchestration, session state, and workflow persistence</li><li><b>Advanced RAG pipelines</b>, including:</li><li>Chunking strategies</li><li>Embedding model selection</li><li>Hybrid search</li><li>Metadata filtering</li><li>Query rewriting</li><li>Reranking</li><li>Context compression</li><li>Retrieval evaluation</li><li>Hallucination mitigation</li><li><b>Memory architecture</b>, including:</li><li>Short-term memory</li><li>Long-term memory</li><li>User-specific memory</li><li>Vector memory</li><li>Persistent knowledge stores</li><li><b>LLM guardrails</b>, including:</li><li>Prompt injection protection</li><li>Permission-aware retrieval</li><li>Output validation</li><li>Policy checks</li><li>Tool execution safety</li><li>Response verification</li><li><b>LLM observability and evaluation</b>, including:</li><li>Tracing</li><li>Prompt/version management</li><li>Eval datasets</li><li>Regression testing</li><li>Latency analysis</li><li>Cost monitoring</li><li>Failure analysis</li><li><b>Enterprise integrations</b>, including REST APIs, databases, CRMs/ERPs, document stores, webhooks, queues, and workflow engines</li><li><b>Vector databases</b> such as Qdrant, Weaviate, Pinecone, Milvus, Chroma, pgvector, Elasticsearch, or OpenSearch</li><li><b>Secure deployment architectures</b> for private cloud, on-premise, offline, or government-secure environments</li><li><b>Node.js basics</b>, including API development, async workflows, service integration, and connecting AI systems to backend applications</li></ul><p><b>Important Note</b></p><p>This role is <b>not for someone who has only built a basic chatbot or RAG over a few PDFs</b>.</p><p>We are looking for someone who can architect real <b>agentic AI systems</b> with:</p><ul><li>Agents</li><li>Tools</li><li>Memory</li><li>Retrieval</li><li>Validation</li><li>Orchestration</li><li>Security</li><li>Monitoring</li><li>Production deployment</li></ul><p>Work location:</p><p>Abu Dhabi - in office</p><p>Job Type: Full-time</p><p>Pay: AED10,000.00 - AED11,000.00 per month</p><p>Application Question(s):</p><ul><li>What is the difference between a basic RAG chatbot and an agentic AI system?</li><li>⁠How would you handle user permissions when the agent retrieves documents from multiple departments?</li><li>How would you evaluate and audit an agent&rsquo;s decisions, tool calls, and retrieved sources in production?</li></ul><p>Experience:</p><ul><li>AI Agent &amp; Routing Engineer: 2 years (Required)</li></ul><p>Language:</p><ul><li>English (Required)</li></ul><p>Work Location: In person</p>

AI Systems Architect & Developer

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