Agentic AI Architect

Inizio Partners Corp • New York, NY

1d

About The Position

We are seeking an experienced Agentic AI Architect to define and lead the architecture for our agentic AI-enabled platform. This role involves designing end-to-end solutions across data, AI, orchestration, and integration layers. You will be responsible for defining integration architecture, designing configurable frameworks, and establishing API/microservices patterns. The role also includes hands-on development, leading technical execution, guiding engineering teams, and driving technical decisions. A key focus will be on AI safety, governance, and establishing ModelOps and PromptOps frameworks to ensure explainability, auditability, and traceability of AI outputs. You will also define the strategic use of GenAI versus deterministic logic and agentic workflows versus pipeline workflows, establish multimodal integration approaches, and design the prompt lifecycle, evaluation, and optimization strategy.

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.
• Bachelor's or Master's in Computer Science, Engineering, Data Science, or related field.
• Hands-on architect with ability to balance strategy + execution.
• GenAI & Agentic Frameworks: Semantic Kernel/ LangGraph (or similar orchestration frameworks); LLM integration (Azure OpenAI, OpenAI APIs, etc.); Prompt engineering, prompt lifecycle design.
• Retrieval & RAG: Azure AI Search (indexing, vector search, hybrid search); Embedding pipelines and retrieval optimization; RAG design, grounding strategies, context management.
• Tool Access & Integration: MCP (Model Context Protocol) architecture and tool design; API design (FastAPI / REST / microservices); Integration with enterprise systems and third-party APIs.
• AI Safety & Governance: NVIDIA NeMo Guardrails; Microsoft Presidio (PII detection/masking); Guardrails for prompt injection, hallucination control.
• Evaluation & ModelOps: Azure AI Foundry (model hosting, versioning, monitoring); Evaluation frameworks (LLM-as-judge, test datasets); Prompt/version control, cost/latency monitoring.
• DevOps & Observability: CI/CD pipelines (Azure DevOps / GitHub Actions); Logging, monitoring, observability (App Insights, etc.); Performance tuning and scalability.

Nice To Haves

• Insurance / reinsurance / financial services domain experience.

Responsibilities

• 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).
• Perform hands-on development and 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.
• Define AI safety and guardrails (PII, hallucination control, policy constraints).
• Establish ModelOps and PromptOps frameworks.
• Ensure explainability, auditability, and traceability of AI outputs.
• Define end-to-end architecture for agentic AI-enabled platform across data, AI, orchestration, and integration layers.
• Design and govern agentic orchestration framework for multi-step workflows.
• Establish architecture patterns for RAG and grounding, Vector search and retrieval, MCP tool access layer, prompt management and evaluation.
• Define where and how to use GenAI vs deterministic logic, agentic workflows vs pipeline workflows.
• Establish multimodal integration approach combining structured, unstructured, and external data.
• Design prompt lifecycle, evaluation, and optimization strategy.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior