Principal AI Developer / Product Architect

Steampunk•McLean, VA

1d•$165,000 - $220,000

About The Position

We are seeking a highly experienced Principal AI Developer / Product Architect to define and lead the technical vision for enterprise-grade AI systems across our client engagements. This role operates at the intersection of architecture, engineering excellence, product strategy, and mission impact. The Principal AI Developer / Product Architect provides authoritative expertise on large-scale generative and predictive AI solutions, drives architectural standards, and mentors teams in designing secure, reliable, scalable AI applications. This leader ensures our AI products deliver measurable mission value while adhering to technical best practices, governance frameworks, and user-centered design principles.

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 Architecture, or a related technical field.
8+ years of hands-on software engineering, ML/AI development, or advanced technical architecture experience.
Demonstrated mastery of modern AI development frameworks, such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, and agent orchestration tools.
Extensive experience architecting and delivering production-grade AI systems involving LLMs, RAG, vector stores, fine-tuning, pipelines, multimodal models, and/or advanced ML workflows.
Strong experience designing cloud-native architectures using AWS, Azure, or GCP, including distributed compute, secure networking patterns, and container orchestration (Docker, Kubernetes).
Expertise in API design, microservice architectures, system integration patterns, and backend engineering.
Deep understanding of AI governance, model safety, evaluation methodologies, and regulatory compliance expectations.
Exceptional communication and influencing skills with the ability to simplify complex technical concepts for executive, technical, and mission audiences.
Proven ability to lead technical strategy, guide engineering teams, and drive architectural alignment across multiple programs.
Track record of mentorship, thought leadership, and raising engineering maturity across an organization.

Nice To Haves

Preferred certifications: AWS/Azure/GCP Architect, ML Specialty, Databricks ML Professional, NIST AI RMF Practitioner (AISIC), NVIDIA DLI certificates, or equivalent architecture-focused credentials.

Responsibilities

Serve as the primary architect for complex AI systems, including multi-LLM orchestration, retrieval-augmented generation (RAG), agentic workflows, multimodal pipelines, and predictive ML architectures.
Translate mission and business needs into actionable AI product architectures, technical roadmaps, and feature strategies.
Lead cross-disciplinary technical design reviews, ensuring that solutions meet standards for reliability, safety, performance, and maintainability.
Architect scalable AI microservices, APIs, and integration patterns that fit within enterprise cloud ecosystems (AWS, Azure, GCP).
Collaborate with product management, UX, and mission stakeholders to define AI-enabled capabilities, prioritize features, and identify innovation opportunities.
Provide hands-on technical leadership for prototyping advanced AI features, evaluating emerging models, and assessing feasibility of new product directions.
Guide engineering teams in implementing core AI components, including LLM pipelines, vector databases, embedding strategies, knowledge stores, evaluation loops, and safety guardrails.
Partner with LLMOps, Evaluation, and Governance teams to ensure secure deployment, continuous monitoring, and compliance with AI safety and governance policies.
Establish and champion best practices in AI architecture, software engineering, DevSecOps, MLSecOps, and responsible AI principles.
Mentor senior developers, support skill development, and elevate engineering and architectural maturity across the AI & Data Exploitation Practice.
Evaluate emerging technologies, foundational models, industry trends, and research—driving adoption strategies and advising leadership on innovation pathways.
Serve as a senior technical advisor in client discussions, helping executives understand architectural tradeoffs, risk profiles, and AI product investment decisions.