AI Developer

Steampunk•McLean, VA

6d•$115,000 - $145,000

About The Position

In today’s rapidly evolving technology landscape, an organization’s data has never been a more important aspect in achieving mission and business goals. Our AI & Data Exploitation experts work with our clients to support their mission and business goals by creating and executing a comprehensive data strategy using the best technology and techniques, given the challenge. At Steampunk, our goal is to build and execute a data strategy for our clients to coordinate data collection and generation, to align the organization and its data assets in support of the mission, and ultimately to realize mission goals with the strongest effectiveness possible. For our clients, data is a strategic asset. They are looking to become a facts-based, data-driven, customer-focused organization. To help realize this goal, they are leveraging visual analytics platforms to analyze, visualize, and share information. At Steampunk you will design and develop solutions to high-impact, complex data problems, working with the best and data practitioners around. Our data exploitation approach is tightly integrated with Human-Centered Design and DevSecOps.

Requirements

Ability to hold a position of public trust with the U.S. government.
Bachelor’s, Master’s, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field.
2+ years of hands-on software engineering experience, with exposure to AI/ML, generative AI, or LLM-driven application development.
Strong proficiency in Python and modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, or similar.
Demonstrated ability to design and develop production-grade AI applications, including APIs, back-end services, orchestration logic, and front-end integrations (when needed).
Experience implementing RAG architectures, embeddings, vector stores, and context retrieval patterns.
Familiarity with multi-agent orchestration frameworks, prompt engineering strategies, and advanced LLM interaction design.
Strong understanding of cloud platforms (AWS, Azure, GCP), including compute, serverless services, and security fundamentals for AI workloads.
Working knowledge of containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for AI-based systems.
Experience with structured and unstructured data, document processing, and application integration with existing enterprise systems.
Understanding of responsible AI principles including safety, fairness, privacy, and model risk mitigation.
Strong analytical and communication skills with the ability to collaborate across engineering, design, and mission domains.
A collaborative mindset and a commitment to raising the technical quality of development work.

Responsibilities

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices.
Implement reusable AI components, libraries, and APIs that streamline application development and accelerate delivery across programs.
Integrate AI models with enterprise systems, APIs, data platforms, vector databases, and cloud-native services to deliver scalable mission capabilities.
Drive iterative experimentation, prototyping, and model improvement cycles in collaboration with Data Scientists and AI Evaluation Scientists.
Design and implement advanced prompt strategies, context management layers, retrieval systems, and LLM orchestration logic.
Build scalable inference services, optimize model performance, and collaborate with LLMOps to enable robust deployment, monitoring, and continuous improvement.
Translate user needs and mission workflows into intuitive, reliable AI-powered features through active partnership with designers and product teams.
Implement secure-by-design and trustworthy AI practices, including safety guardrails, input sanitization, content filtering, and integration of evaluation metrics.
Contribute to internal AI frameworks, code patterns, and shared accelerators that raise delivery quality across the AI & Data Exploitation Practice.
Participate in code reviews and support engineering excellence across multi-disciplinary AI delivery teams.
Stay current with emerging AI techniques, libraries, foundation models, and agent frameworks, evaluating their applicability to client missions.
Contribute to the growth of our AI & Data Exploitation Practice!