Agentic AI Architect
About The Position
We are seeking an experienced Agentic AI Architect to define the end-to-end architecture for our agentic AI-enabled platform. This role involves leading technical execution across AI, data, and platform teams, guiding engineers, and ensuring alignment with architectural vision. The ideal candidate will have a strong background in designing enterprise-scale platforms and distributed systems, with a focus on GenAI and agentic frameworks. You will be responsible for establishing architecture patterns, designing integration strategies, and ensuring the safety, governance, and operational excellence of our AI systems.
Requirements
- 10–15+ years in software/data/AI engineering.
- 4–6+ years in AI/ML/GenAI architecture.
- Strong experience in designing enterprise-scale platforms and distributed systems.
- Hands-on architect with ability to balance strategy + execution.
- Experience with GenAI & Agentic Frameworks: Semantic Kernel/ LangGraph (or similar orchestration frameworks).
- Experience with LLM integration (Azure OpenAI, OpenAI APIs, etc.).
- Experience with Prompt engineering, prompt lifecycle design.
- Experience with Retrieval & RAG: Azure AI Search (indexing, vector search, hybrid search).
- Experience with Embedding pipelines and retrieval optimization.
- Experience with RAG design, grounding strategies, context management.
- Experience with Tool Access & Integration: MCP (Model Context Protocol) architecture and tool design.
- Experience with API design (FastAPI / REST / microservices).
- Experience with integration with enterprise systems and third-party APIs.
- Experience with AI Safety & Governance: NVIDIA NeMo Guardrails; Microsoft Presidio (PII detection/masking); Guardrails for prompt injection, hallucination control.
- Experience with Evaluation & ModelOps: Azure AI Foundry (model hosting, versioning, monitoring).
- Experience with Evaluation frameworks (LLM-as-judge, test datasets).
- Experience with Prompt/version control, cost/latency monitoring.
- Experience with DevOps & Observability: CI/CD pipelines (Azure DevOps / GitHub Actions).
- Experience with Logging, monitoring, observability (App Insights, etc.).
- Experience with Performance tuning and scalability.
Nice To Haves
- Domain experience in Insurance / reinsurance / financial services.
Responsibilities
- Define end-to-end architecture for an agentic AI-enabled platform across data, AI, orchestration, and integration layers.
- Design and govern the agentic orchestration framework for multi-step workflows.
- Establish architecture patterns for RAG and grounding, Vector search and retrieval, MCP tool access layer, and prompt management and evaluation.
- Define integration architecture across Lakehouse, ODS, document systems, underwriting systems, and third-party APIs.
- Design a configurable, metadata-driven framework for multi-LOB onboarding.
- Define API/microservices patterns (Python/.NET hybrid).
- Determine where and how to use GenAI versus deterministic logic, and agentic workflows versus pipeline workflows.
- Establish a multimodal integration approach combining structured, unstructured, and external data.
- Design the prompt lifecycle, evaluation, and optimization strategy.
- Define AI safety and guardrails (PII, hallucination control, policy constraints).
- Establish ModelOps and PromptOps frameworks.
- Ensure explainability, auditability, and traceability of AI outputs.
- Lead technical execution across AI, data, and platform teams.
- Guide engineers (AI, data, full-stack) and ensure alignment with architecture.
- Drive technical decisions and stakeholder communication.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Associate degree
