AECOM is looking to design, develop, and deploy enterprise-grade AI solutions that drive transformation across its global consulting business, specifically focusing on GenAI, ML, and agentic AI systems.
Requirements
- At least 4 years of experience in ML or AI systems design and architecture
- Proven expertise in designing and deploying enterprise-grade genAI, RAG models, agentic AI, and ML pipelines.
- Working knowledge/experience with interoperability protocols such as Model Context Protocol (MCP) and Agent-to-Agent (A2A) for cross-platform agent communication.
- Experience designing/implementing solutions with agentic frameworks (e.g., LangChain, Azure AI Agent Services, n8n, Autogen, etc.).
- Working knowledge of AI Gateway implementation for enforcing guardrails, monitoring, and centralized model access control.
- At least 3 years of experience building AI solutions in AWS or equivalent
- Ability to build AI POCs and design for enterprise production
Responsibilities
- Define and maintain the overarching GenAI, LLMs, RAG pipelines, and autonomous agent systems
- Design and implement multiple agent orchestration workflows and agentic frameworks.
- Evaluate and select AI/Agentic tools, frameworks, and platforms (ex: LangChain, Semantic Kernel, Vertex AI, Azure OpenAI, AWS Bedrock, LangGraph, CrewAI)
- Align architectural decisions with business performance metrics, latency, security, cost, and explainability requirements.
- Assess emerging AI technologies and trends, recommending their adoption where appropriate
- Design scalable architectures that support composability, modularity, observability, and scalability of AI solutions, ensuring alignment with business strategy, data strategy, and technology roadmap
- Embed responsible AI principles, privacy, and governance frameworks into system design
Other
- This position will offer flexibility for hybrid work schedules to include both in-office presence and telecommute/virtual work to be based in Dallas or Houston, TX.
- Collaborate with cross-functional teams, including data architects, data scientists, enterprise architecture, security, AI product managers, and business stakeholders
- Excellent collaboration and communication skills are key
- Must be comfortable engaging with key stakeholders and IT top-level leadership
- Proven ability to lead and influence cross-functional teams, including software engineer teams and software product managers
