Sr. AI Engineer

Berkley • Manassas, VA

1d

About The Position

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

Requirements

• 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.

Nice To Haves

• 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

Responsibilities

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 1,001-5,000 employees