Lead Forward Deployed Engineering, Data Science & Integration

What you'll do

• Design, build, and deploy tailored data science and integration solutions for defense and intelligence missions on-site.
• Architect enterprise integration solutions using platforms like MuleSoft to manage API design and event-driven patterns.
• Develop and deploy workflow automation solutions using tools like Regrello to model complex operational processes.
• Build and implement scalable production ML systems, including predictive models and LLM-augmented workflows.
• Own the entire data lifecycle by performing strategic data modeling and constructing ETL/ELT pipelines.
• Lead rapid prototyping and develop MVPs side-by-side with customer teams to demonstrate technical capabilities.
• Work with customer IT and security teams to accelerate Authority to Operate (ATO) and production go-lives.
• Mentor junior engineers and share lessons learned to shape playbooks and reusable data science assets.

What we're looking for

• Must be a U.S. citizen (U.S. born or naturalized) living on U.S. soil who does not hold dual citizenship.
• Must be eligible for and willing to obtain a U.S. Security Clearance and pass a federal government Minimum Background Investigation.
• Must be able to travel 50-75% of the time to customer sites, including classified facilities.
• 8+ years of experience in a hands-on, end-to-end delivery role for high-quality, scalable production solutions.
• Strong background in Computer Science, Data Science, or a related engineering discipline.
• Expert-level proficiency in one or more programming languages such as Python, Java, or SQL.
• Extensive experience building and deploying AI/ML solutions, including MLOps pipelines, LLM integration, and agentic frameworks.
• Demonstrated expertise in enterprise integration platforms (e.g., MuleSoft) and workflow orchestration platforms (e.g., Regrello) (preferred).