Applied Ai Engineer

AECOM is seeking an Applied AI Engineer to join their Applied AI team, contributing to transformative AI-enabled delivery across clients' projects. The role involves designing, building, and scaling practical AI solutions that unlock measurable business value across infrastructure, environmental, and urban development sectors.

Key Responsibilities:

• Design, build, and deploy AI-enabled solutions addressing real client and project problems.
• Deploy and operate AI solutions on Microsoft Azure, including model hosting, search and retrieval services, serverless and container compute, secrets management, identity and private networking.
• Develop agentic and multi-step workflows, integrating AI with client data and systems.
• Build and maintain Model Context Protocol (MCP) servers and tool interfaces.
• Integrate diverse data sources into reliable, tested pipelines.
• Host, configure, and optimise local and private large language models for clients.
• Build retrieval-augmented generation and document-intelligence pipelines.
• Optimise token usage, latency, and cost through model selection, prompt caching, batching, and incremental processing.
• Establish evaluation, testing, and monitoring practices for AI solutions.
• Design data models, dashboards, and reports presenting AI outputs clearly.
• Apply security, data protection, and responsible AI practices.
• Turn successful solutions into reusable, configurable components.
• Document work through specifications, implementation plans, and post-delivery reviews.
• Support bids and proposals by shaping AI solutions to client requirements.
• Mentor colleagues and support AI training programmes.
• Present work outputs to technical and non-technical audiences.

Qualifications:

• Minimum 3-5+ years of experience in software engineering, data engineering, or applied machine learning.
• Strong proficiency in Python and SQL, with experience building APIs, data pipelines, and automated tests.
• Experience developing LLM applications with tool use, structured outputs, retrieval-augmented generation, agent orchestration, and prompt design.
• Understanding of Microsoft Azure and experience deploying AI solutions on it.
• Proven ability to influence non-technical stakeholders and communicate complex concepts clearly.