AI Platform Engineer

Kimley-Horn•Dallas, TX

1d•Onsite

About The Position

Kimley-Horn is looking for an AI Platform Engineer to join our Dallas, Texas (TX) office! This is not a remote position. In this role, you will help build and maintain the AI platform foundation that makes our firmwide AI solutions scalable, secure, measurable, and supportable. You will work alongside a small, high-impact team that manages enterprise AI platforms (Microsoft 365 Copilot, ChatGPT Enterprise, Claude) for nearly 10,000 employees across more than 150 offices in North America. This is a hands-on mid-level platform engineering role. You will help operate platform components, build retrieval pipelines, support governance patterns for AI agents, and contribute to the telemetry that helps leadership understand adoption, value, and cost. If you like building the systems that other people build on top of, this is the job. Platform Infrastructure• Support and optimize enterprise AI platforms and model access, including Microsoft 365 Copilot, Azure OpenAI Service, and Anthropic Claude• Support on-premises model hosting where required (vLLM, Ollama, or similar)• Operate platform components in Azure AI Foundry and work with AWS Bedrock or other cloud AI services as needed• Help implement security controls for AI platforms, including data handling, access policies, and guardrails Retrieval and Knowledge Architecture• Build and optimize RAG pipelines end to end: embeddings, chunking strategies, vector storage, retrieval, and evaluation• Work with Azure AI Search or comparable vector search platforms• Develop reusable retrieval templates and reference patterns that speed up future knowledge-based solutions across the firm• Support retrieval deployments for internal teams and client-facing use cases, including work within security and compliance boundaries Agent Governance and Enablement• Support governance across the firm’s agent ecosystem: Copilot Agents, Copilot Studio, Power Platform, GPTs, Claude-based solutions, and ServiceNow agents• Contribute to approved patterns for MCP (Model Context Protocol) servers, integrations, and agent interoperability at the platform level• Contribute to operational playbooks for agent lifecycle management, from request intake through deployment and monitoring Telemetry and Reporting• Build and maintain dashboards for AI platform adoption, usage metrics, value tracking, and cost management• Contribute to telemetry and observability pipelines that give leadership clear visibility into how AI tools are being used across the firm• Produce standardized reporting that supports business cases and ongoing platform investment decisions Applied AI Engineering• Build agentic workflows, tool-calling patterns, and multi-step orchestration to solve real engineering consulting problems• Contribute to agent frameworks, reusable components, and development standards that other teams can build on• Support advanced and client-driven use cases, including RAG deployments with specific constraints around data handling and security

Requirements

3+ years in platform engineering, cloud infrastructure, or AI/ML operations
Hands-on experience with Azure AI Search or comparable vector search platforms
Working knowledge of RAG pipeline architecture: embeddings, chunking, retrieval, and evaluation
Experience with Azure AI Foundry, Azure OpenAI Service, or similar managed AI platforms
Familiarity with agentic workflows, tool use, and agent frameworks
Strong scripting and automation skills (Python, PowerShell, or similar)
Bachelor’s degree in Computer Science, Information Technology, or a related field, or equivalent experience

Nice To Haves

Experience with Copilot Studio, Power Platform, or Microsoft 365 agent development
Familiarity with AWS Bedrock, Docker, Kubernetes, or other cloud and container deployment patterns
Experience with on-premises model hosting (vLLM, Ollama, or similar)
Knowledge of MCP (Model Context Protocol), API integrations, or agent interoperability standards
Background in telemetry, observability, or reporting pipelines
Experience in engineering, construction, or professional services environments

Responsibilities

Support and optimize enterprise AI platforms and model access, including Microsoft 365 Copilot, Azure OpenAI Service, and Anthropic Claude
Support on-premises model hosting where required (vLLM, Ollama, or similar)
Operate platform components in Azure AI Foundry and work with AWS Bedrock or other cloud AI services as needed
Help implement security controls for AI platforms, including data handling, access policies, and guardrails
Build and optimize RAG pipelines end to end: embeddings, chunking strategies, vector storage, retrieval, and evaluation
Work with Azure AI Search or comparable vector search platforms
Develop reusable retrieval templates and reference patterns that speed up future knowledge-based solutions across the firm
Support retrieval deployments for internal teams and client-facing use cases, including work within security and compliance boundaries
Support governance across the firm’s agent ecosystem: Copilot Agents, Copilot Studio, Power Platform, GPTs, Claude-based solutions, and ServiceNow agents
Contribute to approved patterns for MCP (Model Context Protocol) servers, integrations, and agent interoperability at the platform level
Contribute to operational playbooks for agent lifecycle management, from request intake through deployment and monitoring
Build and maintain dashboards for AI platform adoption, usage metrics, value tracking, and cost management
Contribute to telemetry and observability pipelines that give leadership clear visibility into how AI tools are being used across the firm
Produce standardized reporting that supports business cases and ongoing platform investment decisions
Build agentic workflows, tool-calling patterns, and multi-step orchestration to solve real engineering consulting problems
Contribute to agent frameworks, reusable components, and development standards that other teams can build on
Support advanced and client-driven use cases, including RAG deployments with specific constraints around data handling and security

Benefits

Exceptional Retirement Plan: 2-to1- company match on up to 4% of eligible compensation (salary + bonus) and additional profit-sharing contribution.
Comprehensive Health Coverage: Low-cost medical, dental, and vision insurance options.
Time Off: Personal leave, flexible scheduling, floating holidays, and half-day Fridays.
Financial Wellness: Student loan matching in our 401(k), and performance-based bonuses.
Professional Development: Tuition reimbursement and extensive internal training programs.
Family-Friendly Benefits: New Parent Leave, family building benefits, and childcare resources.

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