AI Developer

Steampunk•McLean, VA

1d•$145,000 - $185,000

About The Position

We are seeking an experienced AI Developer to serve as a technical authority and product-focused subject-matter expert across our predictive and generative AI solution portfolio. This role will provide expert guidance on the architecture, design, development, and delivery of enterprise-grade AI applications—spanning LLM-powered systems, RAG pipelines, agents, multimodal solutions, and custom machine learning models. The AI Developer / Product SME will work closely with engineering, product, UX, evaluation, governance, and client leadership to define AI capabilities that meaningfully support mission outcomes.

Requirements

Ability to hold a position of public trust with the US government.
Bachelor’s degree and 10 years of experience OR Master's degree and 8 years of experience
Advanced working SQL knowledge and experience working with relational databases, query authoring and optimization (SQL) as well as working familiarity with a variety of databases.
Hands-on experience with LLMs and Generative AI (OpenAI, Bedrock, etc.)
Strong experience with frameworks (e.g., PyTorch, TensorFlow, LangChain)
Experience building production-grade AI systems
Python and API-driven architecture experience
Cloud experience (preferably AWS)
Conversational AI / chatbot experience
Vector databases, embeddings, and RAG patterns
Experience in secure/regulatory environments

Responsibilities

Serve as the senior technical expert for the design and implementation of production AI systems, advising teams on architecture, model selection, orchestration strategies, and optimal development patterns.
Lead the creation of scalable, reusable AI components, services, and frameworks that accelerate delivery across the organization.
Partner with product teams to translate mission challenges into well-defined AI-enabled features, workflows, and technical requirements.
Provide deep expertise on LLMs, embedding models, fine-tuning techniques, agentic systems, and retrieval-augmented generation (RAG) architectures.
Guide engineering teams on best practices for prompt engineering, context management, document processing, evaluation-driven iteration, and safe system design.
Collaborate with LLMOps teams to ensure robust deployment patterns, monitoring strategies, inference optimization, and lifecycle management of AI models and pipelines.
Conduct technical reviews, validate solution designs, and ensure alignment with enterprise architecture, governance policies, and client goals.
Mentor senior engineers and guide teams through complex AI development challenges with a focus on software engineering excellence and user-centered design.
Stay current with emerging AI technologies, research, frameworks, and foundational models; evaluate their suitability for client missions and incorporate learnings into practice standards.
Act as an expert advisor in client-facing discussions, helping stakeholders understand capability tradeoffs, risks, and opportunities associated with AI solutions.
Contribute to the development of accelerators, design patterns, internal best-practice guides, workshops, and training to expand AI delivery maturity across the practice.