Staff Platform Engineer, True Anomaly

• Typically 8+ years of software engineering, DevOps, or cloud engineering experience with a track record of technical leadership, including owning roadmaps, making architectural decisions, and mentoring engineers
• Strong 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
• Experience with large language model APIs, including prompt engineering, tool use, retrieval-augmented generation (RAG), or agent frameworks (e.g. CrewAI, Pydantic AI)
• Demonstrated ability to work across a broad technical surface area, context-switching between infrastructure, application development, and platform architecture. Ability to work across teams to understand requirements and seek consensus
• Demonstrated experience owning technical roadmaps and making architectural decisions that affect multiple teams or products, including setting technical standards and driving adoption
• Experience with building and using modern software development lifecycle best practices (CI/CD pipelines, continuous testing and monitoring)
• Experience deploying and operating production workloads to cloud environments (AWS, Azure, GCP)
• Strong communication skills and ability to translate technical AI concepts for non-technical audiences through training, documentation, and direct support
• Self-directed and comfortable operating with high autonomy in a fast-paced environment where priorities shift and the playbook is being written in real time
• US Citizenship and ability to obtain and maintain a Top-Secret security clearance

Desirable

• As a Staff AI Platform Engineer, you will be one of the first hires to build the infrastructure, tooling, and integrations that put AI directly into the hands and workflows of every team across the company
• This is not a research role. It is a building role. You will ship capabilities that engineers, program managers, operators, and business teams use every day to move faster and produce better work
• The scope is broad by design. Your work will range from building connectors between AI models and internal systems, developing custom applications for a specific business workflow, and more
• You will own platform-level technical decisions about AI providers, tools, and architectures
• You will also help build and deliver AI training and enablement for the company, including office hours, brown bags, and hands-on resources
• The platform engineering org, reporting to the Chief Security Officer, will work across the enterprise, from engineering and product to marketing and finance
• You will have meaningful autonomy, visibility to executive leadership, and the opportunity to shape how a fast-growing defense technology company operates with AI
• As a technical leader on the team, you’ll be expected to bring a breadth of cross discipline experience from areas like cloud infrastructure, DevOps, systems design, technical decision making, operations, and working across organizational boundaries to move the needle for customers
• You will use your broad skillset to partner with senior leaders to deliver AI capabilities to the company
• You will mentor other engineers to promote their growth. You will work through significant ambiguity to establish technical requirements and deliver results for internal stakeholders
• Lead the design of AI platform infrastructure that will be rolled out across the enterprise. Work with stakeholders across business functions to gather requirements, evaluate technical tradeoffs, and reach consensus
• 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
• Own technical evaluation and selection of AI providers, tools, and platforms, making build-vs-buy decisions based on capability, compliance requirements, and speed to value
• Act as a mentor and role model for other engineers on the team to support their growth
• Contribute to AI training and enablement programs for the company, including hands-on workshops, office hours, documentation, and shared resources that help teams build real fluency
• 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 bring informed recommendations on new models, tools, and capabilities that could accelerate the company