Sr. AI Engineer
W. R. Berkley
Senior AI Engineer
This role is focused on building, testing, and operating AI-enabled features and services. Senior AI Engineers deliver production code: implementing services and agentic workflows, wiring up retrieval-augmented generation (RAG) pipelines, integrating with web applications, and instrumenting systems for reliability, security, and cost.
Responsibilities include:
- Build Python services and microservices (APIs, workers) that expose AI capabilities; write clean, tested, maintainable code.
- Implement end-to-end RAG pipelines: connectors, parsing, chunking, embeddings, indexing, and retrieval using Azure AI Search and/or Pinecone.
- Create and operate agentic workflows with LangGraph, n8n, or Agent Development Kit; iterate on prompts/flows and automate offline/online evaluations
- Integrate AI into web applications (REST/GraphQL, events) with attention to input/output validation, rate limiting, and graceful degradation.
- Own CI/CD and containerization for your services; add telemetry (logs/metrics/traces), dashboards, and alerts; participate in on-call/incident response
- Apply Responsible AI, data protection, and access controls; contribute guardrails (filters, red-teaming, PII handling) in code.
- Collaborate with analysts, QA, and product owners to refine requirements; demo increments and incorporate feedback in an agile cadence
- Travel for this position is approximately 5-10%.
Qualifications include:
- 5+ years of professional software engineering experience.
- 3+ years of hands-on applied AI/LLM engineering delivering agentic AI production systems.
- Proficiency in Python and modern engineering practices (testing, linting, typing, packaging, CI).
- Experience with Cloud AI platforms like Azure AI Foundry, GCP Vertex and AWS Bedrock.
- Hands-on experience with vector databases and search algorithms.
- Solid experience with containers and CI/CD; practical AI observability (logs/metrics/traces) and production support mindset.
- Developed multi-agent systems using MCP and A2A technologies.
- Hands on experience with Agentic AI development tools like Cursor, Claudecode and Github copilot.
- Clear, concise communicator able to collaborate with analysts, QA, architects, and business stakeholders.
- Experience with AI Observability in platforms like Datadog and Langsmith.
- Bachelor's degree with emphasis in related field or equivalent experience.
Qualifications that are not required but are a plus:
- Familiarity with knowledge graphs (e.g., Neo4j) and graph queries (e.g., Cypher)
- Experience leveraging and training NLP models
- Experience fine-tuning LLMs and VLMs
- Experience with LLM evaluation frameworks like DeepEval and RAGAs
Behavioral core competencies:
- Critical Thinking
- Customer Service Oriented
- Technically Astute
- Business Knowledge
- Influential
- Conceptual Thinking
- Personal Ownership
The Company is an equal employment opportunity employer.
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