AI Deployment Engineer

AI Deployment Engineer

The Role: AI Deployment Engineer Location: United States | Work Mode: Remote / Field-Present | Employment Type: Full Time

About Forward Deployed Engineering Aurigo's central platform team builds the AI agents. Forward Deployed Engineering works alongside agencies to deploy them into production, ensure they perform reliably, and evolve them as customer needs change. The team bridges product innovation and real world operations, turning AI capabilities into measurable outcomes for public infrastructure agencies. As an AI Deployment Engineer, you are the technical core of that mission.

Role Overview Aurigo is looking for an AI Deployment Engineer to join its Forward Deployed Engineering team. This is a hands on deployment and integration role, not a model development role. You will lead the technical deployment of AI agents into customer environments, integrating them with enterprise systems, validating their performance, and ensuring they deliver reliable outcomes in production. You will work directly with agency tech teams, business stakeholders, and Aurigo's Product and Engineering teams to solve technical challenges, optimize deployments, and continuously improve how AI is adopted across customer workflows. Every deployment helps shape the playbooks, tooling, and best practices that make future deployments faster, more scalable, and more successful. Travel is a core part of this role as you will regularly work alongside customers during deployment, adoption, and expansion.

What You'll Do: Agent Deployment & Integration Configure and deploy Aurigo AI agents within customer Masterworks environments — tailoring agent behavior, workflows, and outputs to each agency's specific requirements Build and maintain data integrations between Masterworks and agency systems: scheduling tools, cost systems, financial management platforms, document management, GIS, and agency data warehouses Develop scripts and lightweight automation to streamline agency data workflows, reduce manual handoffs, and prepare data for agent consumption Work with agency IT staff, data stewards, and system administrators to navigate access, permissions, and integration constraints in government technology environments Troubleshoot deployment issues in the field — diagnosing root causes, implementing fixes, and documenting solutions for reuse across future deployments Configuration, Monitoring & Outcomes Configure deployed agents in Aurigo's agent builder — setting workflow logic, prompts, output formats, and thresholds so each agent matches how the agency actually works, in close collaboration with the Agent Designer and domain SME Connect agents to agency data — build and maintain the integrations and data-preparation steps that feed clean, structured inputs from Masterworks and connected systems into each agent Monitor agents in production — track output quality against the outcomes each agent is contracted to deliver, catch degradation or drift early, and adjust configuration to keep performance on target Diagnose and resolve deployment and performance issues in the field — identify root causes, implement configuration or integration fixes, and document them for reuse across future deployments Feed field learnings back to the central AI platform team — when an agent needs a capability that configuration alone cannot provide, you are the channel that turns that into a product request, so the fix ships once and improves every account

Requirements: Candidate Profile Bachelor's degree in Computer Science, Engineering, AI, or related field from a premier institution. Master's degree preferred. 3+ years in a hands-on technical delivery role — solutions or deployment engineering, systems integration, or implementation engineering — putting software into real production environments where reliability matters Strong integration and scripting skills: connecting enterprise systems through REST APIs, moving and reshaping data between platforms, and automating data-preparation workflows (Python or comparable) Hands-on comfort configuring and operating modern AI agent or LLM-based tools — prompt and workflow configuration, agent setup, and judging whether outputs are reliable; you do not need to have trained models, you need to be excellent at making already-built agents perform Experience working with unstructured and semi-structured data — PDFs, XML exports, structured logs — and preparing it so downstream systems and agents can consume it Ability to work independently in ambiguous field environments — you diagnose and build without waiting for a perfectly scoped ticket Preferred Experience Experience monitoring software or model performance in production — spotting drift or degradation and acting on it before it affects the customer Experience with construction, infrastructure, or capital program data — cost codes, schedule structures, contract document formats, or similar domain data Prior work in a field deployment, systems integration, or technical consulting role — you have built in client environments under real constraints Familiarity with agent platforms or retrieval/vector search from a configuration-and-integration standpoint (Pinecone, Weaviate, pgvector, or equivalent) Experience in government or regulated environments — navigating IT procurement, access controls, and security requirements Public Trust clearance eligibility About Aurigo Aurigo is an AI-native capital program management platform trusted by over 300 customers managing more than $300 billion in capital programs across North America. With over 40,000 projects delivered, Aurigo helps organisations in transportation, water and utilities, healthcare, higher education, and government plan, build, and manage infrastructure with confidence. Recognised as one of the Top 25 AI Companies of 2024 and a Great Place to Work for three consecutive years, we leverage artificial intelligence to create smarter, more connected outcomes. At Aurigo, we don't just build software — we help shape the future of infrastructure.