R&D Software Engineer — AI/ML Mission Solutions

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, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics.