Software Engineer designing and implementing backend features for customer - facing AI workflows. Collaborating on system integrations and ensuring production reliability in a fast - paced environment.
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.
Requirements
- 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.
Benefits
- competitive healthcare coverage
- wellness programs
- take it when you need it time off
- parental leave
- recognition programs
- much more!
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