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AECOM · 3 weeks ago

Agentic AI Architect - Hybrid (Dallas or Houston TX)

Dallas, TX

Full-time

Hybrid

Senior Level, Lead/Staff

$190K/yr - $220K/yr

10+ years exp

AECOM is a global infrastructure consulting firm dedicated to delivering a better world. They are seeking a hands-on Agentic AI Architect to design, build, and optimize enterprise-grade AI platforms, utilizing advanced AI architecture and cloud technologies. The role requires collaboration with cross-functional teams and a focus on innovation in AI-driven platform development.

Civil EngineeringConstructionConsultingEnergyGovernmentInformation Technology

No H1B

Responsibilities

Define and evolve the enterprise AI platform architecture, breaking down business and functional requirements into scalable, secure, and maintainable technical designs

Establish the long-term architecture runway for AI products, owning POCs, design spikes, and forward-looking evaluations of emerging technologies— including agentic architectures, orchestration frameworks, and tool-use patterns

Apply expertise in distributed systems and API design to ensure the platform is robust, observable, and simple to extend

Ensure best practices in secure coding, performance optimization, resilience, and lifecycle maintainability

Architect and implement enterprise-grade RAG (Retrieval Augmented Generation) pipelines, including vector search, embeddings, knowledge stores, and LLM orchestration

Design and operationalize agentic workflows, including multi-agent collaboration, tool-calling agents, planner/executor patterns, and automated reasoning loops

Build and integrate production-grade AI agents capable of interacting with external tools, APIs, enterprise systems, and knowledge sources

Utilize the Model Context Protocol (MCP) to expose internal tools, datasets, and enterprise APIs to LLMs in a secure, governed manner

Integrate and operationalize multiple LLM providers (Azure OpenAI, OpenAI, Anthropic, open-source models) into production systems

Leverage Azure AI services— Semantic Kernel, Kernel Memory, AI Foundry, Cognitive Search—to enable intelligent, context-aware platform capabilities

Design, deploy, and optimize cloud-native AI applications in Azure with emphasis on cost efficiency, observability, resilience, and security

Partners with enterprise architects, product managers, developers, and data engineers in an Agile/Scrum environment to ensure architecture aligns with product strategy

Provide hands-on mentorship on AI development patterns—including agent-building, RAG troubleshooting, prompt design, vector search patterns, and orchestration frameworks

Conduct architecture reviews, code reviews, and design sessions to drive engineering quality and consistency

Translate business needs into scalable platform capabilities that support long-term product and enterprise roadmaps

Stay current on rapidly evolving AI trends: multi-agent systems, model orchestration, tool-use protocols, evaluation frameworks, prompt engineering, latency optimization, and AI safety approaches

Recommend improvements to development, testing, deployment, and estimation processes to increase delivery velocity while maintaining quality and compliance

Establish platform-level governance patterns including architectural guardrails, reusable modules, MCP tool adapters, and standardized agent templates

Champion experimentation, rapid prototyping, and continuous adoption of modern AI engineering practices to increase the organization’s AI maturity

Qualification

Agentic WorkflowsAzure CloudC#SQL ServerAngularAI frameworksMCPRetrieval Augmented GenerationAPI ManagementAgile mindsetProblem solvingCollaborationCommunication

Required

BA/BS plus at least 10 years of professional architecture experience in full-stack platforms or demonstrated equivalency of experience and/or education

Hands-on architect abilities to collaborate with current Agile SCRUM team

Ability to work with little guidance on POCs and forward-looking research on upcoming AI technologies

Strong front-end experience with Angular (latest versions preferred)

Expertise in SQL Server including complex queries, performance tuning, and data modeling

Hands-on experience with Azure Cloud services including monitoring and troubleshooting Cloud issues

Practical experience with Agentic Workflows, AI Agents, MCP, API Management (APIM), Semantic Kernel, Kernel Memory, AI Foundry, or similar AI frameworks

Familiarity with LLM integration and Retrieval Augmented Generation (RAG) architectures

Strong understanding of software engineering principles, design patterns, and platform architecture

Preferred

Experience with architecting AI platforms

Observability, alerting and scaling applications with more than 50K users

Knowledge of containerization (Docker), DevOps practices (CI/CD pipelines in Azure DevOps/GitHub Actions)

Prior work on AI-driven platforms in production environments including chatbots

Background in machine learning concepts (vector databases, embeddings, prompt engineering)

Exposure to multimodal AI capabilities such as: Voice-to-Text (speech recognition), Text-to-Speech (natural voice generation), Image-to-Text (OCR, vision-to-language), Other modalities (audio, video, and sensor data AI applications)