Senior Platform Engineer, AI

Responsibilities

• Build and maintain AI platform infrastructure: API integrations, model access pipelines, system connectors (MCP, tool use), and on-premises compute environments as needed
• Develop custom AI-powered applications, workflows, and integrations that connect frontier models to internal systems such as project management, documentation, communications, and operational tools
• Contribute to technical evaluation and selection of AI providers, tools, and platforms, helping inform build-vs-buy decisions based on capability, compliance requirements, and speed to value
• Help design and deliver AI training and enablement programs for the company, including hands-on workshops, office hours, documentation, and shared resources that build real fluency across teams
• Partner with engineering, security, and IT teams to ensure AI deployments meet government security and compliance requirements across data classification levels
• Stay current with the rapidly evolving AI landscape and surface new models, tools, and capabilities that could accelerate the company

Qualifications

• Typically 5+ years of software engineering, DevOps, or cloud engineering experience building and shipping production systems, with demonstrated ability to work independently and deliver complex projects with minimal guidance
• Software engineering or similar background with experience building and shipping production systems, ideally in Python, TypeScript, or similar languages common in AI/ML tooling
• Experience using the latest AI powered development tools to deliver production code and automate routine tasks. You can read, write, and understand code in common programming languages like Python, Typescript, Java, etc.
• Experience with large language model APIs, including prompt engineering, tool use, retrieval-augmented generation (RAG), or agent frameworks (e.g. CrewAI, Pydantic AI)
• Experience building integrations between software systems using APIs, webhooks, data pipelines, or authentication flows
• Able to work across a broad technical surface area, moving between infrastructure, application development, and platform work as priorities require
• Effective communication skills and ability to explain technical AI concepts to non-technical audiences through training, documentation, or direct support
• Comfortable operating with autonomy in a fast-paced environment where priorities shift and the playbook is being written in real time

Preferred Skills And Experience

• Experience deploying AI or ML systems in government, defense, or regulated environments with security and compliance constraints
• Experience deploying and operating production workloads to cloud environments (AWS, Azure, GCP). Familiarity with government cloud environments (AWS GovCloud, Azure Government) and authorization frameworks (FedRAMP, NIST 800-53, IL4/IL5)
• Background in developer tooling, platform engineering, or internal tools teams at high-growth technology companies
• Experience building knowledge retrieval systems, embedding pipelines, or enterprise search infrastructure
• Experience contributing to technical roadmaps and architectural decisions that affect multiple teams or products
• Active U.S. Secret or Top-Secret security clearance