R&D Software Engineer — AI/ML Mission Solutions
Rackner · Remote
📍 Remotevia greenhousePosted 2026-06-25
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R&D Software Engineer — AI/ML Mission Solutions
Location: United States
Work Model: Remote
Travel: Approximately 15% for R&D events, technical demos, and collaboration sessions
Clearance: U.S. citizenship required. Active Secret clearance preferred; candidates must be eligible to obtain and maintain a U.S. government security clearance.
Build AI/Data Capabilities for Mission-Focused R&D
Rackner is hiring an R&D Software Engineer — AI/ML Mission Solutions to help build, prototype, validate, and improve AI/data-driven software capabilities for defense-relevant use cases.
This is a hands-on R&D role for an engineer who enjoys solving hard problems across software, data, AI/ML, algorithms, RAG, agentic systems, simulation, or pipeline workflows. You will work with Rackner’s internal R&D team to turn ambiguous ideas, operational needs, and user feedback into working technical capabilities.
We are not looking for one person to be an expert in every area. The strongest candidates bring one deep technical lane — such as AI/ML systems, RAG/agentic workflows, data pipelines, Python/Go development, Kubernetes/deployable systems, MLOps, or algorithmic software — plus enough working knowledge in adjacent areas to contribute in a fast-moving R&D environment.
This is not a traditional sales role and not a platform-only engineering role. Kubernetes, Terraform, cloud, CI/CD, and DevSecOps are helpful, but the main focus is software engineering, AI/data systems, algorithmic problem-solving, validation, and R&D execution.
What You'll Do
Design, prototype, test, and refine AI/data-driven software capabilities for mission-focused use cases
Build software for AI/ML experimentation, RAG or agentic workflows, model integration, simulation, data pipelines, and applied R&D prototypes
Develop and improve data workflows, schema transformations, JSON workflows, APIs, backend services, and integration layers
Support AI/ML workflows including inference, evaluation, deployment, monitoring, and model-serving patterns
Validate outputs through testing, data quality checks, evaluation methods, debugging, monitoring, and failure analysis
Troubleshoot complex issues across software, data, model, and integration layers
Work with engineers and technical leadership to assess tradeoffs, identify constraints, and improve solution design
Participate in technical demos, R&D events, mission-user discussions, and feedback cycles as needed
Convert stakeholder or mission feedback into actionable technical steps
Clearly explain technical concepts to engineering teams, program stakeholders, customers, and mission users
What You’ll Bring
Strong software engineering background with hands-on experience building, testing, debugging, and improving modern systems
Proficiency in Python, Go, C++, Java, SQL, or a similar language used for backend, data, AI/ML, or algorithmic work
Hands-on depth in at least one relevant area: AI/ML systems, RAG, agentic development, LangChain, data pipelines, MLOps, algorithmic software, simulation, or deployable systems
Ability to clearly explain what you personally built, how the system worked, what broke, how you validated it, and what impact it had
Familiarity with real-world data workflows, including data sources, APIs, schemas, transformations, databases, files, events, or logs
Comfort working in fast-paced environments with evolving requirements
Willingness to travel approximately 15% for R&D events, demos, collaboration sessions, or customer and mission engagements
Experience That Stands Out
DoD, Air Force, Platform One, Big Bang, mission planning, C2, ISR, autonomy, or defense technology experience
AI/ML systems, applied AI workflows, RAG, agentic development, LangChain, model integration, evaluation, deployment, serving, registry, or monitoring
MLOps tools or workflows such as MLflow, SageMaker, Databricks, Kubeflow, Airflow, Dagster, Prefect, or similar tools
Data pipelines, ETL/ELT workflows, schema transformations, JSON transformations, dbt pipelines, or messy data integration workflows
Data validation, data quality checks, pipeline monitoring, failure handling, debugging, or observability for data/model workflows
Algorithms, optimization, simulation, scientific computing, applied mathematics, physics-informed software, computer vision, autonomy, or robotics
Python, Go, C++, SQL, PyTorch, TensorFlow, scikit-learn, FastAPI, Postgres, or related software/data/AI tooling
Technical demos, pilots, field exercises, workshops, briefings, or customer / mission-user discussions
Cloud, Docker, Kubernetes, Terraform, CI/CD, DevSecOps, ATO, or secure delivery experience
About Rackner
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 and technical teams collaborate closely with leadership, program teams, and mission stakeholders to design, demonstrate, and improve software systems that address complex operational challenges.
Benefits & Perks
Rackner invests in its people, because when you grow, we all win.
Company-supported certifications aligned to current and future program work, including cloud, Kubernetes, DevSecOps, security, AI/ML, project management, and related technical areas
Clear advancement tracks and future leadership opportunities
401(k) with 100% match up to 6%
Comprehensive medical, dental, vision, life, and disability coverage
Generous PTO and paid holidays
Home-office equipment plan and remote work support
Fitness and wellness reimbursement
Weekly pay schedule and modern perks, including team events
Equal Opportunity
Rackner is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, se
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