Staff AI Engineer (Acquia DAM)

About the role

The role of AI Staff Engineer within R&D involves driving the technical evolution of Acquia DAM, a market-leading platform that transforms content management using powerful AI features.

Responsibilities

• Write and ship production AI code daily.
• Architect agentic AI workflows using LangGraph, Temporal, Pydantic — stateful, multi-agent workflows at enterprise scale.
• Own AI observability via LangFuse: tracing, prompt versioning, evaluation, and performance benchmarking across all model interactions.
• 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.

Requirements

• 8+ years of software engineering with 3+ years in production of AI Agents.
• Hands-on LangGraph, Temporal, Pydantic expertise — stateful, cyclic, multi-agent workflows at enterprise scale.
• Hands-on LangFuse expertise - tracing, evaluation, prompt management, and dataset-driven testing.
• 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.

Desired Skills

• Enterprise SaaS or CMS, including familiarity with Acquia's Drupal-based DXP experience.
• Agentic development workflow fluency — AI-assisted coding tools (Copilot, Cursor, Claude) as everyday accelerators.
• Familiarity with persistent agent runtimes - such as OpenClaw and Hermes Agent, understanding cross-session memory, autonomous skill creation, and always-on agent infrastructure as it matures in enterprise contexts.
• LLM fine-tuning or model evaluation experience and awareness of foundational model tradeoffs.
• Human-in-the-loop — interrupt-driven agents and enterprise design.
• Strong communication skills — able to present AI system design to both engineers and C-suite stakeholders.
• Senior IC track record — known for the quality of your own code and system designs, with mentoring that happens organically through great work, not through meetings.