Director of Platform Engineering (VOR)

hatch I.T. is partnering with Expression to find a Director of Platform Engineering (VOR). See details below: About The Role: Expression is seeking a Director Platform Engineering to lead the architecture, development, and scaling of VOR, their flagship platform that unifies data, workflows, and AI agents to drive decision-making in complex, high-stakes environments. This is not a management-only role. You will write code, review pull requests, debug production issues, and make hands-on architectural decisions alongside the team you build. You will own VOR's technical direction end-to-end from system design and infrastructure to adoption and mission impact while personally contributing to the codebase in meaningful ways. You will lead cross-functional teams to deliver a platform that integrates seamlessly into client environments, operationalizes AI, and drives measurable outcomes across government and enterprise programs. About the Company: Founded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community. Expression’s “Perpetual Innovation” culture focuses on creating immediate and sustainable value for their clients via agile delivery of tailored solutions built through constant engagement with their clients. Expression was ranked #1 on the Washington Technology 2018's Fast 50 list of fastest growing small business Government contractors and a Top 20 Big Data Solutions Provider by CIO Review. country: US all locations: [DMV] commitment: Full Time department: Featured Hatch Accounts location: DMV team: Expression Responsibilities: : Hands-On Engineering & Architecture Personally architect and code critical platform components you set the technical standard by building, not just directing Own system design decisions across VOR's data integration, workflow orchestration, and AI agent layers Conduct code reviews, set engineering standards, and establish patterns that scale across the platform Debug and resolve complex production issues spanning cloud infrastructure, distributed systems, and AI pipelines Maintain deep technical fluency in the full stack: Python, NodeJS, Go, cloud-native services (AWS GovCloud), container orchestration, data pipelines, and LLM/agent frameworks Platform Strategy & Execution Own the end-to-end strategy, roadmap, and delivery of the VOR platform Drive the evolution of VOR across data integration, workflow orchestration, and AI/agent capabilities Ensure alignment between product vision, engineering execution, and mission needs Make build-vs-buy decisions grounded in hands-on technical evaluation, not slide decks Productization & Scale Lead the transition from services-driven delivery to a scalable, repeatable platform model Define deployment models across hybrid cloud, enterprise, and edge environments Establish platform standards for interoperability with systems like Palantir, Databricks, and Snowflake Build and maintain CI/CD pipelines, testing infrastructure, and release processes that support rapid, reliable delivery AI Operationalization Drive the "last mile" of AI ensuring models and data systems are embedded into real workflows, not just prototyped Architect and implement human-in-the-loop systems that balance automation with control, explainability, and trust Oversee VOR Agents development, ensuring mission alignment and compliance through auditable, explainable, and traceable actions. Drive the implementation of evaluation frameworks, agent behavior monitoring, and red-teaming to ensure agentic systems behave safely and predictably within mission constraints. Stay current with and personally evaluate emerging AI/ML frameworks, tools, and techniques Customer & Mission Delivery Partner with program teams and clients to implement VOR in real-world environments Translate complex mission requirements into platform capabilities Ensure successful deployment from pilot to production, personally engaging at breakdown points when needed Team Leadership Build and lead a high-performing team of engineers, architects, and product leaders Foster a culture of technical excellence, ownership, and shipping — lead by example at the keyboard Mentor engineers through pairing, code review, and architectural guidance Align cross-functional teams across engineering, delivery, and business units Qualifications: : Bachelor's degree in Computer Science, Engineering, or related discipline 10+ years of experience in platform engineering, data systems, or AI/ML delivery, with progressive leadership responsibility Currently hands-on: you write production code today, not five years ago Proven track record of building and scaling platforms not just managing teams that do Deep proficiency in Python, Go, NodeJS and modern cloud-native development (AWS required; Azure/GCP a plus) Experience with containerization, orchestration (Kubernetes/ECS), and infrastructure-as-code Working knowledge of data platforms (e.g., Databricks, Snowflake, Spark) and workflow orchestration frameworks Experience with AI/ML lifecycle and operationalization — MLOps, model serving, LLM integration, agent architectures Experience working in complex, regulated, or mission-driven environments (government, defense, or national security preferred) Ability to bridge deep technical execution with executive communication and client engagement Experience in client-facing roles including pre-sales and delivery engagements Preferred Qualifications: : Master's degree in Computer Science, Software Engineering, or related field Active TS/SCI clearance Experience with FedRAMP, IL4/IL5+, or ATO processes Hands-on experience with generative AI, multi-agent systems, or retrieval-augmented generation (RAG) Contributions to open-source projects or a visible engineering track record Relevant certifications (AWS Solutions Architect, Kubernetes, etc.) Working knowledge of Agentic AI frameworks (e.g., LangChain, LangGraph, CrewAI, or similar). Familiarity with retrieval and context engineering systems and vector search systems/vector database integration.