About The Position
We are seeking an experienced Agentic AI Architect to design, build, and deploy advanced AI solutions leveraging Generative AI and agentic frameworks. This role will focus on integrating Large Language Models (LLMs) and implementing robust retrieval, tool access, safety, and evaluation mechanisms. You will be instrumental in shaping the future of our AI capabilities, ensuring they are safe, efficient, and scalable.
Requirements
- Expertise in GenAI & Agentic Frameworks (Semantic Kernel/LangGraph or similar orchestration frameworks).
- Proficiency in LLM integration (Azure OpenAI, OpenAI APIs, etc.).
- Strong skills in prompt engineering and prompt lifecycle design.
- Experience with Retrieval & RAG, including Azure AI Search (indexing, vector search, hybrid search), embedding pipelines, and optimization.
- Knowledge of RAG design, grounding strategies, and context management.
- Experience with Tool Access & Integration, including MCP architecture, tool design, API design (FastAPI/REST/microservices), and integration with enterprise systems.
- Familiarity with AI Safety & Governance tools (NVIDIA NeMo Guardrails, Microsoft Presidio for PII detection/masking, prompt injection, hallucination control).
- Experience with Evaluation & ModelOps, including Azure AI Foundry (model hosting, versioning, monitoring), evaluation frameworks (LLM-as-judge, test datasets), and prompt/version control.
- Proficiency in DevOps & Observability, including CI/CD pipelines (Azure DevOps/GitHub Actions), logging, monitoring (App Insights, etc.), and performance tuning.
Responsibilities
- Design and implement agentic AI systems using frameworks like Semantic Kernel or LangGraph.
- Integrate various LLMs, including Azure OpenAI and OpenAI APIs.
- Develop and optimize Retrieval-Augmented Generation (RAG) pipelines, including embedding, indexing, and retrieval strategies.
- Design and implement tool access mechanisms and integrate with enterprise systems and third-party APIs.
- Implement AI safety and governance measures using tools like NVIDIA NeMo Guardrails and Microsoft Presidio.
- Establish and manage AI evaluation frameworks and ModelOps practices.
- Develop and maintain CI/CD pipelines for AI solutions.
- Ensure observability, performance tuning, and scalability of AI systems.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
