Hiring.Camp

Sr. AI Engineer

Berkley

·

Apr 23, 2026

Location
Manassas, VA, US
Department
IT
Experience
5+ years
Closing date
Today
Source
iCIMS

Description

Company Details

 

Company URL: https://www.berkleytechnologyservices.com/ 

 

Berkley Technology Services (BTS) is the dynamic technology solution for W. R. Berkley Corporation, a Fortune 500 Commercial Lines Insurance Company. With key locations in Urbandale, IA and Wilmington, DE, BTS provides innovative and customer-focused IT solutions to the majority of WRBC’s 60+ operating units across the globe. BTS’s wide reach ensures that ideas and opinions are considered at every level of the organization to guarantee we find the best solutions possible.  

 

Driven by a commitment to collaboration, BTS acts as consultants to our customers and Operating Units by providing comprehensive solutions that not only address the challenge at hand, but proactively plan for the “What’s Next” in our industry and beyond.  

 

With a culture centered on innovation and entrepreneurial spirit, BTS stands as a community of technology leaders with eyes toward the future -- leaders who truly care about growing not only their team members, but themselves, and take pride in their employees who shine. BTS offers endless ways to get involved and have the chance to grow your career into a wide range of roles you'd never known existed. Come join us as we push forward into the future of industry leading technological solutions.  

 

Berkley Technology Services: Right Team, Right Technology, Simple and Secure.  

Responsibilities

The Sr. AI Engineer 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.

 

  • 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

Qualifications

  • 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

Skills

PythonAWSAzureGCPCI/CDNLPGitHubRESTGraphQLMicroservices

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