Senior GenAI Engineer

Senior GenAI Engineer

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• We are seeking a hands-on GenAI Engineer to join a team developing production-grade, AI-powered solutions for a major US insurance provider.
• Designed and developed an enterprise-grade Generative AI platform using Python, FastAPI, and FastMCP to automate recruitment workflows and provide intelligent candidate insights. Built scalable, production-ready APIs that integrated with OpenAI GPT and Anthropic Claude models for candidate screening, resume analysis, job matching, and automated recruiter assistance.
• Implemented RAG (Retrieval-Augmented Generation) pipelines using vector databases such as Pinecone/Milvus to provide context-aware responses from enterprise knowledge repositories. Developed AI Agents and custom plugins/skills to automate candidate engagement, interview scheduling, talent recommendations, and workflow orchestration.
• Owned the complete application lifecycle, including architecture design, API development, deployment, monitoring, observability, logging, and performance optimization. Leveraged AI-assisted development tools such as Claude, Codex, and VS Code to accelerate development, debugging, code reviews, and delivery.

Responsibilities

• Design and deliver production-grade GenAI solutions using OpenAI GPT and Anthropic Claude models.
• Build agentic workflows using LLM orchestration frameworks such as LangChain, LangGraph or similar, including multi-step reasoning, tool use and human-in-the-loop patterns.
• Design and implement RAG pipelines covering document ingestion, chunking, embeddings, hybrid search, re-ranking and retrieval quality tuning.
• Develop MCP servers using FastMCP to expose enterprise tools and data to AI agents.
• Create and extend Skills and Plugins that adapt LLM capabilities to insurance-specific workflows.
• Work with vector databases to support semantic search and knowledge retrieval.
• Implement LLM evaluation, guardrails and safety controls, including hallucination detection, prompt injection protection and PII handling.
• Implement observability and diagnostics for LLM systems: tracing, evaluations, token and cost tracking, latency and quality monitoring.
• Build scalable backend APIs in Python and FastAPI that serve GenAI capabilities to client applications.
• Own the full lifecycle of GenAI applications: prototyping, development, deployment, monitoring and continuous improvement.
• Use AI-assisted development tools (Claude, Codex) as a core part of the daily engineering workflow.
• Advise client stakeholders on GenAI feasibility, solution design, cost and model selection.

Skills

Must have

• GenAI experience (primary focus):
• 2+ years of hands-on GenAI engineering experience, with at least one LLM-based solution delivered to production.
• Deep practical experience integrating OpenAI GPT and Anthropic Claude: prompt engineering, tool/function calling, structured outputs, streaming and context management.
• Proven experience designing, building and tuning RAG pipelines in real-world projects.
• Hands-on experience building agentic solutions with LangChain, LangGraph, LlamaIndex or similar frameworks.
• Practical experience with MCP servers (FastMCP preferred) and LLM extension mechanisms such as Skills and Plugins.
• Hands-on experience with at least one vector database (e.g., Pinecone, Weaviate, Qdrant, Chroma, pgvector, Azure AI Search).
• Experience with LLM observability and evaluation tooling (e.g., LangSmith, Langfuse, Arize Phoenix, OpenTelemetry).
• Understanding of LLM limitations and risks: hallucinations, prompt injection, cost and latency trade-offs, and model selection.
• Engineering:
• 4+ years of professional software development experience with a strong focus on Python.
• Solid experience building production REST APIs with FastAPI.
• Experience deploying and running applications in production: Docker, CI/CD and at least one major cloud platform (AWS, Azure or GCP).
• Daily, confident use of VS Code and AI coding assistants such as Claude and Codex.
• Upper-Intermediate (B2) or higher English, with the ability to communicate directly with US-based stakeholders.

Nice to have

• Experience applying GenAI in insurance or financial services (e.g., claims automation, document understanding, underwriting assistance).
• Experience with fine-tuning, embeddings optimization or open-source LLMs.
• Experience with multi-agent architectures and agent-to-agent communication.
• Kubernetes and infrastructure-as-code (Terraform, Bicep).
• Knowledge of responsible AI practices and compliance requirements for PII in regulated industries.

Other

Languages

English: B2 Upper Intermediate

Seniority

Senior

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