Enterprise AI Platform Architect

Role overview

Acquia is seeking an Enterprise AI Platform Architect to lead the delivery and architecture of production-grade AI agent implementations. You will design and deploy AI systems, run architectural reviews, and set organization-wide engineering blueprints for advanced LLM and agent workflows.

Key responsibilities

• Lead end-to-end delivery of AI agent implementations, including architectural reviews and performance optimization recommendations
• Design and deploy production-grade AI systems and write high-impact code
• Architect stateful, cyclic, multi-agent workflows
• Define engineering blueprints/patterns across the organization, including:
  • RAG architecture patterns
  • Advanced tool-calling approaches
  • Context window optimization
  • Prompt engineering practices
• Benchmark new LLM providers and orchestration frameworks

Requirements

• Deep expertise in generative AI, agents, and agentic architectures
• Ability to design, build, and ship production-grade agentic AI workflows
• 7+ years experience in cloud computing architecture, software engineering, or technical consulting
• Cloud AI deployment experience on AWS, Azure, or GCP, including:
  • containerization
  • inference cost management
• Strong Python proficiency and engineering fundamentals (testing, CI/CD, architecture)
• Hands-on LangGraph experience (stateful, cyclic, multi-agent workflows at enterprise scale)
• Track record of shipping AI applications to production (not only prototypes)
• RAG knowledge, including vector databases, embedding models, and retrieval strategies
• 3+ years in AI/ML platform architecture and development, including 2+ years recent experience in generative AI and agentic architectures for production applications
• Hands-on LangFuse experience (tracing, evaluation, prompt management, dataset-driven testing)

Nice-to-haves

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related field