✦ Luna Orbit — AI & Machine Learning

Principal AI Engineer

at AECOM

📍 Dallas, TX Hybrid Posted April 11, 2026
Type Not Specified
Experience executive
Exp. Years 10+ years
Education Bachelor's Degree
Category AI & Machine Learning

AECOM is hiring a Principal AI Engineer to build production-grade AI systems that integrate into real business workflows. The role combines AI (LLMs, RAG, agents) with distributed systems and backend engineering, with ownership of reliability, latency, and cost in production.

  • Design and build production AI systems end-to-end
  • Own system architecture and implementation for scalability and reliability
  • Integrate LLMs, RAG, and agents into real workflows
  • Build services, APIs, and event-driven systems connecting AI to enterprise platforms
  • Establish observability, evaluation, and feedback loops; debug production issues

This is an end-to-end AI engineering role focused on designing and building scalable, reliable AI-enabled services and APIs using event-driven systems. You will implement observability, evaluation, and feedback loops and debug issues across data, models, infrastructure, and application layers.

The ideal candidate is a hands-on Principal-level AI engineer with 10+ years of software engineering experience, including building and operating production systems where AI/LLMs are a core component. They have strong backend and distributed systems expertise and can design AI-enabled solutions (LLMs, RAG, agents) with robust reliability, latency, cost, and failure-handling practices.

Bachelor's Degree plus at least 10 years of software engineering experiencebuilding and operating production software systemsAI/LLMs as a core componentbackend or distributed systems engineeringservicesAPIsevent-driven systemsdata pipelinesdesigning and implementing AI-enabled systems (e.g.RAGagent-based systems)
integration into real workflows across HRFinanceITand Legalobservabilityevaluationand feedback loops
Production AI systemsdistributed systemsLLMsRAGagentsarchitecturereliabilitylatencycostfailure handlingservicesAPIsevent-driven systemsobservabilityevaluationfeedback loopsdata pipelinesbackend engineering
production AI systemsdistributed systemssystem reliabilitylatencycost optimizationfailure handlingLLMsRAGagentsarchitecture and implementationscalabilitymaintainabilityservicesAPIsevent-driven systemsdata pipelinesobservabilityevaluationfeedback loopsdebugging complex issuesdata modelsinfrastructureapplication layersbackend engineeringenterprise platformsdeployment and operation
hands-onresourcefulcomfortable operating in ambiguitytake ownership of outcomesmove from problem to solutiontechnical direction through your worktechnical leadershipinfluencing how similar systems are designed and built across teamsoperating autonomously
Industry SaaS
Job Function Design and implement production AI systems (LLMs, RAG, agents) integrated with enterprise workflows using distributed backend architectures
Role Subtype AI Engineer
Tech Domains Amazon Web Services, Kubernetes, Python, SQL / PostgreSQL, Azure
Principal AI EngineerAI systemsproduction AI systemsdistributed systemsreliabilitylatencycostfailure handlingLLMsRAGagentsarchitecturedeploymentoperationservicesAPIsevent-driven systemsobservabilityevaluationfeedback loopsdata pipelinesbackend engineeringdebugdebuggingenterprise platformsHRFinanceITLegal

Must have Bachelor's Degree plus at least 10 years of software engineering experience, Must have proven track record of building and operating production software systems with AI/LLMs as a core component, Must have experience with RAG or agent-based systems in real applications

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