About the role

Hands-on Staff AI Engineer developing production-grade agentic AI workflows for Acquia's digital experience platform. Collaborating with teams on AI architectures to meet enterprise requirements.

Responsibilities

Write and ship production AI code daily — you are an active contributor, not just an architect.
Architect agentic AI workflows using LangGraph — stateful, multi-agent workflows built for enterprise scale and reliability.
Own AI observability via LangFuse: tracing, prompt versioning, evaluation, and performance benchmarking across all model interactions.
Set AI engineering standards for agent design patterns, RAG, prompt management, context optimization, and tool-calling strategies.
Partner with product and platform teams to deliver AI architectures that meet enterprise SLA, security, and compliance requirements.
Evaluate and adopt emerging tooling— benchmarking LLM providers, orchestration frameworks, and agentic stack improvements.
Mentor engineers as a natural extension of your work — sharing knowledge through code reviews, pairing sessions, and design discussions, not through management overhead.
Represent Acquia's AI capabilities in customer architectural reviews, technical discovery, and roadmap conversations.

8+ years of software engineering with 3+ years in production AI/ML or LLM systems.
Hands-on LangGraph expertise — stateful, cyclic, multi-agent workflows at enterprise scale.
Hands-on LangFuse expertise - tracing, evaluation, prompt management, and dataset- driven testing
Proficiency with agent harness frameworks such as LangChain or similar (e.g. LlamaIndex, CrewAI) — composing chains, tools, memory, and retrieval pipelines.
Deep Python proficiency and strong engineering fundamentals (testing, CI/CD, architecture).
Cloud AI deployment experience (AWS, Azure, or GCP) including containerization and inference cost management.
RAG architecture knowledge— vector databases, embedding models, and retrieval strategies.
B.S. in Computer Science or equivalent practical experience.