Senior AI Product Engineer

steampunk•McLean, VA

13d•$120,000 - $190,000

About The Position

We are looking for an experienced Senior AI Product Engineer to design, build, and optimize enterprise-grade generative AI applications that combine large-language models, retrieval pipelines, and human-centered design. The ideal candidate is a hands-on engineer who understands both the technical depth of AI systems and the product sensibilities needed to turn them into usable, mission-driven tools. This role bridges engineering, data science, and product strategy across Steampunk’s AI & Data Exploitation practice.

Requirements

Ability to hold a position of public trust with the U.S. government.
Bachelor’s degree and 12 years of experience.
5+ years of experience developing AI or data-driven applications, including at least 2 years building GenAI or LLM-based systems.
Proficiency in Python and frameworks such as LangChain , LlamaIndex , DSPy , or similar orchestration tools.
Demonstrated experience integrating LLMs with retrieval layers, vector databases, or enterprise APIs.
Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization/orchestration tools such as Docker and Kubernetes.
Strong understanding of software engineering principles, version control, CI/CD, and modern DevSecOps practices.
Knowledge of prompt engineering, evaluation metrics, and AI safety concepts (e.g., hallucination detection, red-team testing).
Experience collaborating with designers and product managers to translate user requirements into functional AI experiences.
Excellent communication skills with the ability to articulate technical approaches to both executive and technical stakeholders.
Proven ability to work independently in fast-moving, cross-disciplinary teams while mentoring others and maintaining engineering excellence.

Responsibilities

Design and implement full-stack GenAI applications using LLMs, embeddings, retrieval-augmented generation (RAG), and multi-agent orchestration frameworks.
Collaborate with designers, data scientists, and mission stakeholders to translate business needs into usable, explainable AI capabilities.
Develop reusable AI components and micro-services that accelerate model deployment, context management, and evaluation workflows.
Integrate LLMs with existing enterprise systems and APIs, ensuring scalability, observability, and secure data handling.
Lead prototyping and rapid iteration cycles, applying human-centered design methods to refine AI behavior and user experience.
Collaborate with LLMOps and MLOps teams to ensure automated testing, versioning, monitoring, and continuous improvement of AI models and pipelines.
Evaluate new foundation models, prompt-optimization techniques, and fine-tuning strategies to improve accuracy, efficiency, and safety.
AI governance principles, including bias detection, output validation, and compliance with emerging AI-risk frameworks.
Mentor junior engineers and contribute to the internal AI Engineering Community of Practice by sharing best practices in GenAI archite cture and productization.
Contribute to the growth of our AI & Data Exploitation Practice by shaping reusable patterns and assets for enterprise AI delivery.