Acquia
Staff AI Engineer (Acquia DAM)
Remote-Canada · Staff+
Sponsorship not specifiedDetected 29 days ago
PythonCode ReviewVector DatabasesAWSGCPAzureCI/CDTemporalLLMsRAGAgentic AILangGraphAI OrchestrationCommunicationMentoringAdaptability
About the role
- Write and ship production AI code daily - you are an active contributor.
- Architect agentic AI workflows using LangGraph, Temporal, Pydantic - stateful, multi-agent workflows built for enterprise scale and reliability.
- In this role, you will work to deeply integrate DAM with the broader Acquia AI ecosystem, architecting upcoming roadmap themes centered on autonomous asset governance, agentic orchestration, and smart visual transformations.
Responsibilities
- 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.
- Mentor engineers as a natural extension of your work - sharing knowledge through code reviews, pairing sessions, and design discussions, not through management overhead.
- 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.
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
- 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.
- 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.
This listing is sourced directly from Acquia's careers page and normalized into a canonical job model.