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AECOM

Global infrastructure consulting and program management

Applied AI Engineer

AI Application EngineeringPosted on Nov 13
Full-timeManchester, UKNo salary listed

About the Job

Requirements

  • At least 3 years of experience in software engineering, data engineering, or applied machine learning, including hands-on delivery of large language model-based applications, preferably in infrastructure, engineering, or professional services.
  • Strong proficiency in Python and SQL, with experience building APIs, data pipelines, and automated tests, and using version control and continuous integration and continuous delivery pipelines.
  • Experience developing large language model applications with tool use, structured outputs, retrieval-augmented generation, agent orchestration, and prompt design across commercial and open-weight models.
  • Understanding of Microsoft Azure and experience deploying AI solutions on it, including services such as Microsoft Foundry, Azure AI Search, Azure Functions or Container Apps, Key Vault, Entra ID, and private networking; also experience deploying on private or on-premises infrastructure and managing token usage and cost.
  • Ability to influence non-technical stakeholders and communicate complex concepts clearly, with sound judgement about when AI is and is not the right tool.
  • Experience mentoring and coaching technical teams and promoting collaboration and innovation.

Responsibilities

  • Design, build, and deploy AI-enabled solutions addressing client and project problems, from discovery and proof of concept through production.
  • 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, in line with cloud governance.
  • Develop agentic and multi-step workflows, including orchestration and multi-agent patterns, deciding where deterministic code, AI models, and human review belong.
  • Build and maintain Model Context Protocol servers and tool interfaces that provide AI models secure, least-privilege access to data and systems.
  • Integrate APIs, databases, document repositories, scheduled exports, and streaming feeds into reliable, tested pipelines that adapt to different client environments.
  • Host, configure, and optimize local and private large language models for clients whose data cannot leave their environment, including model selection, quantization, inference serving, and hardware sizing.
  • Build retrieval-augmented generation and document-intelligence pipelines, including optical character recognition, extraction, classification, and cited answers over large, unstructured document sets.
  • Optimize token usage, latency, and cost through model selection, prompt caching, batching, and incremental processing within defined usage budgets.
  • Establish evaluation, testing, and monitoring practices for AI solutions, including evaluation datasets, regression tests, run logs, and accuracy measurement on real data.
  • Design data models, dashboards, and reports that clearly present AI outputs to project teams and decision-makers.
  • Apply security, data protection, and responsible AI practices, including prompt-injection defenses, data-residency controls, and human-in-the-loop review, aligned with global standards.
  • Turn successful solutions into reusable, configurable components that can be deployed for multiple clients with minimal rework.
  • Document work through specifications, implementation plans, and post-delivery reviews, capturing evidence of delivered value.
  • Support bids and proposals by shaping AI solutions to client requirements, writing technical responses, estimating effort and running costs, and preparing demonstrations for client presentations and interviews.
  • Mentor colleagues and support AI training programs, fostering safe and effective AI adoption.
  • Present outputs to technical and non-technical audiences, translating complex AI concepts and limitations into clear, lay terms.

Desired Qualifications

  • Preferably have experience in infrastructure, engineering, or professional services.
  • Be familiar with the Model Context Protocol, multi-agent frameworks, evaluation harnesses, and large language model observability tools.

About the Company

AECOM

Global infrastructure consulting and program management

AECOM is a global infrastructure consulting firm that provides a wide range of services, including architecture, design, construction management, engineering, environmental services, and program management, to government agencies, private companies, and non-profits. Its work centers on managing and delivering large-scale infrastructure projects, from planning and design to construction and operation, with fees tied to the project type and scope. Unlike firms with a narrower focus, AECOM offers end-to-end support across transportation, buildings, cities, and overall infrastructure, combining technical expertise with project oversight and sustainability considerations. The company aims to improve the world by enhancing natural and social systems, promoting equity and inclusion, and driving responsible, lasting outcomes for communities.

Company size
10,001+
Company stage
IPO
Headquarters
Dallas, TX
Founded
1990

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