Sr. AI Engineer

Berkley•Los Angeles, CA

160d•$146,000 - $271,000

About The Position

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. Travel for this position is approximately 5-10%.

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