Frontier AI Research Engineer, Lead

Booz Allen Hamilton•McLean, VA

1d•Remote

About The Position

Frontier AI Research Engineer, Lead The Opportunity: Frontier Research operates at the edge of what’s possible to convert breakthrough capabilities into real-world impacts. Frontier Research functions as both a strategic radar and an execution engine, turning frontier AI capabilities into differentiated IP, new product directions, and transformational business opportunities. The Lead Engineer is a senior technical builder who drives the architectural rigor and engineering execution behind Frontier Research prototypes and integrations. This role is responsible for designing, building, and validating advanced AI systems across the full stack. The Lead Engineer translates frontier concepts into working systems, ensures technical excellence across prototypes, and serves as the lab’s senior-most hands-on engineering authority. If you are passionate about building distributed AI systems, architecting agentic applications, and transforming cutting-edge research into production-grade capabilities - this role is for you.

Requirements

5+ years of experience in deep technical engineering
Experience designing and building advanced AI systems, including managing them
Experience developing AI prototypes, products, or high‑visibility technical demonstrations
Experience leading technical exchanges and evaluations with commercial partners and executive stakeholders
Experience with translating research into scalable, revenue‑generating solutions
Experience guiding R&D efforts from concept through implementation
Ability to create and drive technical roadmaps aligned with organizational goals
Ability to display high creativity, intellectual curiosity, and enthusiasm for showcasing innovative AI capabilities
Bachelor’s degree

Nice To Haves

Experience scaling AI systems from prototype to enterprise-grade product environments
Experience in a leadership role of multidisciplinary engineering or research teams delivering high‑impact technical outcomes
Experience building or advising AI‑driven businesses, including monetization strategies and go‑to‑market planning
Experience with driving innovation programs, incubators, or R&D portfolios
Experience with cloud-native AI infrastructure, MLOps, or large-scale model deployment
Experience as a thought leader in AI, including speaking at technical keynotes, conferences, or public forums
Ability to engage and influence senior executives, commercial partners, and external stakeholders
Ability to display a record of published research, patents, or conference presentations in AI, ML, or emerging technologies
Ability to maintain a strong network within the AI research or engineering community to support recruiting and partnership development
Master's degree in Computer Science, Engineering, AI, or a related technical field preferred
Doctorate degree in Computer Science, Engineering, AI, or a related technical field a plus

Responsibilities

Evaluate emerging advancements across hyperscalers, leading AI labs, academia, and venture-backed companies.
Conduct hands-on technical assessments, benchmarks, and proof-of-concepts to validate applicability and performance.
Own the technical delivery of end-to-end AI systems spanning infrastructure, frontier LLMs, agentic and multi-agent applications and physical AI pipelines.
Deliver working systems—not slideware.
Work with business units, to support hands-on integration of emerging AI technologies in complex customer environments such as cloud, hybrid, edge, or disconnected.
Ensure production rigor without sacrificing innovation speed.
Provide day-to-day technical leadership to engineers and researchers.
Conduct design reviews, guide architectural decisions, and raise the overall technical bar of the Applied Research team.
Convert prototype learnings into reusable frameworks, reference architectures, accelerators, and technical artifacts that scale across programs and business units.