Generative AI Engineer

Senior AI/ML Engineer

About the Role

A Silicon Valley-based cloud system integrator working with AWS, Google, and Databricks. We're looking for a Senior AI/ML Engineer to join our flagship AI Platform for life sciences — supporting companies like Pfizer, Moderna, and Novartis in accelerating drug discovery through cloud and AI. You'll help design and deploy production AI systems, from autonomous agents to classical ML pipelines and enterprise AI gateways.

What You'll Do

• Build and deploy multi-agent AI systems (LangGraph, AutoGen, or similar), including tool-calling and MCP (Model Context Protocol) servers/clients.
• Deploy AI Gateway infrastructure to manage LLM routing, cost, and security across providers (OpenAI, Anthropic, Bedrock, Vertex).
• Build end-to-end ML training and deployment pipelines (XGBoost, PyTorch, Databricks/SageMaker) with monitoring for drift and performance.
• Design RAG pipelines and fine-tune open-source LLMs (LoRA/QLoRA) for domain-specific use cases.
• Lead architecture reviews, mentor on MLOps best practices, and collaborate with data engineers on lakehouse pipelines.
• Participate in daily Scrum with a globally distributed team.

What You Bring

• 5+ years in software/AI engineering, including 3+ years focused on AI/ML in production.
• 2+ years deploying classical ML models and/or LLM-based systems at scale.
• Hands-on experience with AI agent frameworks and/or AI Gateway infrastructure.
• Strong Python skills; working knowledge of TypeScript/Node.js for backend APIs.
• Experience with Databricks (Spark, Delta Lake, MLflow, Unity Catalog) and AWS (ECS, Lambda, SageMaker, S3).
• Excellent English communication — able to explain ML systems to both technical and non-technical stakeholders.
• Comfortable working autonomously in a remote team (9 AM–5 PM EST overlap required).

Nice to Have

• AWS ML Specialty, Databricks ML Professional, or Google ML Engineer certification.
• Experience fine-tuning open-source LLMs (Llama, Mistral, Falcon).
• Familiarity with GxP/21 CFR Part 11 compliance in life sciences.
• Contributions to open-source AI/ML or MCP tooling.

What We Offer

• Competitive compensation and benefits.
• Zero legacy infrastructure — work on cutting-edge AI systems.
• Training budget (certifications, hackathons, Udemy/Coursera).
• Access to Claude Code, Codex, Cursor, and frontier model APIs.
• A collaborative team at the intersection of life sciences and applied AI.