Forward Deployment Application Engineer

Quick Facts

• Role: Forward Deployment Application Engineer

Description

Build and deploy AI applications that improve spacecraft engineering, manufacturing, and services. As part of the AI Strike Team, you work directly with engineers and business users to turn prioritized problems into useful software through six-week delivery sprints. You own application delivery from discovery and prototyping through integration, evaluation, deployment, and technical handoff.

Responsibilities

• Embed with users to observe work, map handoffs and bottlenecks, establish baselines, and define an MVP with the Product Lead and domain owner.

• Build application interfaces, backend services, APIs, and workflow automation; put working prototypes in front of users early and improve them through observed use.

• Integrate enterprise and engineering systems through reusable connectors, APIs, and data transformations while preserving permissions, revisions, configuration, units, and provenance.

• Implement retrieval-augmented generation, structured outputs, and tool calling with grounded answers, citations, and explicit human approval where needed.

• Create representative evaluation cases and regression tests; measure task completion, retrieval accuracy, review effort, latency, reliability, and operating cost.

• Deploy through approved GitLab CI/CD and DevSecOps patterns; implement monitoring, error handling, access controls, recovery, and documentation for sustainment.

Requirements

• Bachelor’s degree; four additional years of experience may be substituted for a degree.

• Minimum 15 years of software, application, solutions, or data engineering experience with evidence of shipping and supporting software used by real customers.

• Strong Python and API-development skills; experience building usable application interfaces in TypeScript, JavaScript, or comparable frameworks.

• Hands-on experience delivering LLM applications, including retrieval, structured outputs, tool integration, and evaluation; ability to distinguish model limitations from data, workflow, and software defects.

• Experience integrating APIs, databases, documents, and enterprise systems with practical understanding of authentication, authorization, data modeling, and data quality.

• Proficiency with Git, automated testing, CI/CD, containers, and cloud deployment; ability to debug across application, integration, and infrastructure boundaries.

• Ability to lead technical discovery, explain tradeoffs clearly, work through incomplete requirements, and deliver a bounded solution within a short sprint.

• Sound judgment handling sensitive information, maintaining traceability, and designing workflows with accountable human review.

Benefits

• Drive measurable improvements in cycle time, engineering effort, quality, or program execution using reliable applications in real workflows.

• Work in a six-week sprint model, delivering an evaluated pilot and supporting scale/iteration/stop decisions toward production.