• Design, build, and deploy Microsoft Copilot Studio agents—including topics, knowledge sources, generative orchestration, authentication, and content moderation—that automate enterprise workflows across the bank • Develop and maintain custom Power Platform connectors and MCP (Model Context Protocol) servers that securely expose internal banking systems and APIs to Copilot Studio agents and Power Platform makers • Architect and govern Dataverse solutions—tables, relationships, security roles, business rules, plug-ins, and elastic tables—serving as the system of record for Copilot Studio agents and Power Apps • Build agent tools, plug-ins, and reusable components in C# and .NET 10 to extend Copilot Studio with custom business logic, API integrations, and AI orchestration patterns (tool calling, RAG, declarative agents) • Operate Power Platform Application Lifecycle Management (ALM) at scale—managed environments, solution packaging, the ALM Accelerator, Power Platform CLI (pac), and pipelines integrated with GitHub Actions • Implement responsible AI governance—DLP policies, environment strategy, agent telemetry, evaluation harnesses, content safety, and grounding—ensuring compliance with bank security and regulatory standards • Partner with software, data, and AI engineers to integrate Azure OpenAI, Azure AI Foundry, and Azure AI Search into Power Platform and Copilot Studio solutions, including knowledge ingestion and retrieval pipelines • Mentor pro-code and citizen developers on Copilot Studio patterns, Power Platform ALM, secure coding, and AI engineering best practices; champion compliance with change management and SDLC standards.

• Design, build, and deploy scalable Generative AI platforms and applications. • Develop AI solutions leveraging AI Agents, RAG pipelines, and/or Knowledge Graph architectures. • Write clean, scalable, production-quality code using Python or Java. • Own end-to-end platform development and deployment within a DevOps environment. • Implement and maintain CI/CD pipelines using GitHub Actions and/or Jenkins. • Develop and manage Infrastructure as Code (IaC) using Terraform. • Deploy and manage solutions on AWS serverless services and/or Kubernetes-based infrastructure. • Collaborate with cross-functional teams to improve platform scalability, reliability, performance, and security. • Monitor, troubleshoot, and optimize AI platform operations in production environments. • Stay current with emerging AI technologies and recommend platform improvements and best practices.

• Architect and implement the MLOps strategy for the program • Design and own enterprise-grade ML/LLM pipelines • Build container-oriented ML platforms (GKE-first) • Implement hybrid MLOps + LLMOps workflows • Serve as a technical authority across multiple internal and customer projects • Enable observability, monitoring, drift detection, lineage tracking, and auditability across ML/LLM systems • Collaborate with cross-functional teams to deliver production-ready ML solutions • Ensure all solutions adhere to security, governance, and compliance expectations • Conduct architecture reviews, troubleshoot complex ML system issues, and guide teams through implementation • Mentor engineers and provide guidance on modern MLOps tools

Role Description You'll design and own the scalable, low-latency infrastructure that powers uRun's real-time inference runtime, the platform that makes live, interactive, multi-user AI workloads possible. - This is not classic ops or cloud management; you'll be deep in the AI runtime itself. - Latency, frame rate, and interactive quality of service are first-class platform properties. - The workloads are GPU-constrained, memory-bound, and bursty. - You will often write platform features, custom controllers, and scaling logic. - You will report directly to our founder, Keegan McCallum, and set the technical direction for the engineering organization. Qualifications - 7+ years as an engineer, with a proven track record architecting and owning large-scale production systems. - Deep Kubernetes expertise, including GPU-heavy clusters (NVIDIA tooling, autoscaling on GPU nodes) and service-mesh patterns. - Strong cloud and infrastructure-as-code experience: AWS, GCP, or Azure; Terraform, Pulumi, or equivalent; networking and security (VPC, IAM, API-gateway-style routing). - SRE-style thinking and observability depth: Prometheus/Grafana, OpenTelemetry, distributed tracing, SLOs, incident response, and post-mortems. - Proficiency in at least one of Python, Go, or TypeScript/Node.js for platform tooling, automation, and glue code. - Experience with streaming or real-time systems: WebRTC, low-latency video pipelines, or comparable latency-sensitive workloads. - A track record of mentoring engineers and influencing cross-functional teams. Requirements - Hands-on experience with GPU-constrained, memory-bound, or bursty workloads. - Experience writing custom Kubernetes controllers, scaling logic, or other platform features in-house. - Early-stage startup experience: owning ambiguous problems end-to-end and setting technical direction with limited scaffolding. Benefits - Competitive salary and meaningful equity in an early-stage AI infrastructure company. - Health, dental, and vision — full coverage. - 401(k) — company-supported retirement savings. - FSA/HSA — flexible spending accounts for healthcare costs. - Paid time off — we trust you to manage your time. - Top-tier tooling — access to the best AI tools available: Claude, Codex, Kimi, and whatever else helps you move faster. - MacBook Pro and AirPods — the hardware you need, on us. Company Description We build the stage, not the show. We're an infrastructure company, a developer-tools company, and a production partner for model labs, and focus is a deliberate choice we've made and hold to. - Day-to-day, that means a small team, a high bar, and real ownership. - You won't wait for permission or inherit a backlog of someone else's decisions. - In a founding security role, the function is what you make it. - It also means ambiguity: priorities shift, not everything is documented. - You'll often be the person who decides what "secure enough, for now" means.