Staff AI Engineer

Role Overview

Join Acquia as a Staff AI Engineer to design, build, and ship production-grade agentic AI workflows for the Acquia DXP. You’ll combine engineering excellence with enterprise reliability, observability, and scale.

Key Missions

• Design, build, and ship production-grade agentic AI workflows across the Acquia DXP using LangGraph and LangFuse.
• Own AI observability with LangFuse: tracing, prompt versioning, evaluation, and performance benchmarking across model interactions.
• Set AI engineering standards for:
  • agent design patterns
  • RAG architecture
  • prompt management
  • context optimization
  • tool-calling strategies

Responsibilities / How You’ll Work

• Hands-on engineering across the full agentic workflow lifecycle.
• Mentor other engineers through high-quality work and organic collaboration.
• Represent Acquia’s AI capabilities in customer architectural reviews and technical discussions.

Requirements

• Hands-on LangFuse expertise (tracing, evaluation, prompt management, dataset-driven testing).
• RAG architecture knowledge: vector databases, embedding models, and retrieval strategies.
• 8+ years software engineering experience, including 3+ years in production AI/ML or LLM systems.
• 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.
• Hands-on LangGraph expertise, including stateful, cyclic, multi-agent workflows at enterprise scale.
• Experience with agent harness frameworks such as LangChain (or similar: LlamaIndex, CrewAI) including chains, tools, memory, and retrieval pipelines.
• Familiarity with enterprise SaaS/CMS and Acquia’s Drupal-based DXP.
• Agentic development workflow fluency using AI-assisted coding tools (e.g., Copilot, Cursor, Claude).
• Familiarity with persistent agent runtimes (e.g., OpenClaw, Hermes Agent) and concepts like cross-session memory and always-on agent infrastructure.
• LLM fine-tuning and/or model evaluation experience and awareness of foundational model tradeoffs.
• Human-in-the-loop capabilities (interrupt-driven agents, enterprise design).
• Strong communication skills—able to present AI system design to engineers and C-suite stakeholders.

Nice-to-Haves

• Senior IC track record with a strong reputation for code and system design quality, plus mentoring through execution.
• Experience with persistent agent runtimes as they evolve in enterprise contexts.