About Acquia
Acquia is the digital experience platform built for a world where your audience isn't only human. Its agents too. As AI agents become active participants in how people discover, consume, and act on digital content, Acquia gives enterprise teams the platform to create, manage, and distribute experiences designed for both. Powered by agentic AI that orchestrates — not just advises — Acquia automates complex digital workflows within the governance guardrails large organizations require. The world's #1 Drupal hosting provider, Acquia brings together Content Management, Digital Asset Management, and Product Information Management in a single AI-powered Command Center: Acquia Source. Acquia. Built for every audience, human or otherwise.
The Role
Acquia is seeking an Enterprise AI Architect to join our AI Core Engineering team. The ideal candidate combines deep technical expertise in generative AI, agents, and agentic architectures with the ability to move fast, designing, building, and shipping production-grade agentic AI workflows across the Acquia DXP. We’re scaling Acquia’s agentic orchestration system from alpha to production.
Responsibilities
- Lead end-to-end delivery of AI agent implementations. Write and ship production AI code daily — you are an active contributor.
- Conduct architectural reviews and provide recommendations for optimizing AI agents' performance, scalability, and security.
- Lead the design and deployment of production-grade AI systems as an active contributor writing high-impact code. Expect to live in Python, LangGraph, Temporal, Pydantic and LangFuse to turn vision into reality.
- Architect sophisticated, stateful, multi-agent workflows using LangGraph. You will build the frameworks that allow autonomous agents to operate with enterprise-level reliability and scale.
- Champion AI observability by integrating LangFuse for deep tracing, prompt versioning, and rigorous evaluation. You’ll turn "black box" LLM interactions into transparent, benchmarked performance data.
- Define the engineering blueprints for the entire organization. You will establish patterns for RAG architecture, advanced tool-calling, context window optimization, and prompt engineering.
- As the internal scout for emerging tech, you will benchmark new LLM providers and orchestration frameworks, ensuring our stack remains at the cutting edge of the agentic revolution.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
- 7+ years of experience in cloud computing architecture, software engineering, or technical consulting.
- 3+ years of experience in AI agents architecture and development, with deep recent experience (2+ years) in generative AI and agentic architectures in production applications.
- Demonstrated track record of shipping AI applications to production environments, not just prototypes.
- Hands-on LangGraph, Temporal, Pydantic — stateful, cyclic, multi-agent workflows at enterprise scale.
- Hands-on LangFuse - tracing, evaluation, prompt management, and dataset-driven testing.
- 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.