Senior Technical Lead — AI & Data Mission Systems

Rackner is seeking a Senior Technical Lead — AI & Data Mission Systems to help shape and build emerging R&D capabilities for mission-focused government work.

This is a hands-on technical leadership role for someone who wants to work on hard, ambiguous problems that go beyond traditional product feature development. You will help turn early ideas, complex or imperfect data, and mission needs into working prototypes, data workflows, and software capabilities that can be tested, demonstrated, and improved quickly.

The strongest candidates will bring deep software engineering judgment, strong Python and data systems experience, and the ability to explain technical decisions clearly. This is not a pure ML research role, and it is not a traditional full-stack, cloud, or platform-only role. The work may involve data pipelines, AI/ML workflows, model deployment, schema transformation, validation, simulation, analytics, APIs, and prototype-to-demo development.

In this role, you will have the opportunity to:

• Work on technically challenging R&D problems tied to real mission needs
• Influence early-stage architecture and technical direction
• Build prototypes that can become mission-relevant capabilities
• Apply AI, data, and software engineering skills in a national security and federal innovation environment
• Grow as a hands-on technical leader without moving away from meaningful engineering work

• Lead the design and development of AI/data-enabled mission software prototypes
• Build data workflows from ingestion through transformation, validation, storage, and downstream use
• Work with structured and semi-structured data such as JSON, schemas, APIs, logs, documents, sensor feeds, time-series data, geospatial data, or simulation outputs
• Support model deployment, model serving, model registry, MLOps, experiment tracking, or data/model validation workflows where applicable
• Translate ambiguous research, mission, user, or operational needs into practical technical approaches
• Debug pipeline failures, data quality issues, model/output quality concerns, and system reliability problems
• Explain architecture, tradeoffs, constraints, validation approach, and failure modes to technical and non-technical stakeholders
• Collaborate with R&D engineers, technical leadership, and mission stakeholders through build, demo, feedback, and iteration cycles
• Use cloud, container, CI/CD, and DevSecOps practices where needed to support secure, reliable, and repeatable delivery
• Mentor or guide engineers through technical decisions, prototyping efforts, implementation challenges, and troubleshooting

• Proven background designing, building, or leading software systems involving data pipelines, AI/ML, analytics, simulation, automation, mission data, or complex backend processing
• Strong hands-on Python skills, particularly for data pipelines, backend services, automation, APIs, AI/ML, or pipeline development
• Experience working with structured or semi-structured data such as JSON, schemas, APIs, logs, documents, time-series, sensor, geospatial, or simulation data
• Ability to clearly explain system architecture, data flow, technical tradeoffs, validation strategies, and potential failure modes
• Track record of translating ambiguous technical, research, user, or mission needs into functional software, prototypes, or production systems
• Demonstrated ownership of engineering outcomes from concept through implementation, validation, or operational use
• Comfort working independently in fast-moving, prototype-driven, or uncertain environments
• Strong communication skills with the ability to explain complex technical concepts to technical and non-technical audiences
• Willingness to travel approximately 15% for R&D events, technical demonstrations, collaboration sessions, or mission-focused engagements

• Active Secret clearance or higher
• Background supporting DoD, Air Force, Space Force, mission systems, C2, ISR, autonomy, mission planning, defense software, or national security programs
• End-to-end data pipeline work, including ingestion, transformation, validation, storage, monitoring, and downstream consumption
• Familiarity with MLOps, model deployment, model serving, model registries, experiment tracking, or model monitoring tools such as MLflow, Kubeflow, or similar
• Proficiency with data workflow, orchestration, or processing tools such as Airflow, Argo Workflows, Spark, PySpark, dbt, or similar
• Knowledge of data quality, schema transformation, JSON transformation, data normalization, API-driven data exchange, or validation frameworks such as Great Expectations
• Exposure to mission-relevant data types such as sensor feeds, geospatial data, time-series data, simulation outputs, logs, documents, imagery/video, or other structured and semi-structured formats
• Familiarity with Python-based data or AI tooling such as Pandas, NumPy, PyTorch, TensorFlow, Hugging Face, FastAPI, or similar
• Background in R&D, prototype-driven, defense tech, applied AI, data systems, scientific computing, or mission-focused environments
• Demonstrated ability to collaborate with operators, mission users, customers, or non-engineering stakeholders to understand workflows and translate needs into technical solutions
• Participation in technical demos, pilots, field events, customer discussions, live exercises, or prototype review sessions
• Hands-on work with cloud platforms, containers, Kubernetes, Docker, Terraform, Helm, CI/CD, observability, DevSecOps, or secure software delivery practices
• Track record of leading engineering efforts, shaping architecture decisions, or mentoring engineers through complex technical challenges

Rackner is a software consultancy focused on building mission-critical systems for the U.S. government. Our teams work across cloud platforms, DevSecOps, AI/ML, distributed systems, and modern software engineering initiatives supporting federal agencies and national security missions.

Rackner engineers collaborate closely with technical leadership, program teams, and mission stakeholders to design, build, and improve software systems that address complex operational challenges.

Rackner is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics.