AI Lead Developer (aviation/aerospace)

ALTEN Technology USAHerndon, VA
5hHybrid

About The Position

We’re ALTEN Technology USA, an engineering company helping clients bring groundbreaking ideas to life—from advancing space exploration and life-saving medical devices to building autonomous electric vehicles. With 3,000+ experts across North America, we partner with leading companies in aerospace, medical devices, robotics, automotive, commercial vehicles, EVs, rail, and more. As part of the global ALTEN Group—57,000+ engineers in 30 countries—we deliver across the entire product development cycle, from consulting to full project outsourcing. When you join ALTEN Technology USA, you’ll collaborate on some of the world’s toughest engineering challenges, supported by mentorship, career growth opportunities, and comprehensive benefits. We take pride in fostering a culture where employees feel valued, supported, and inspired to grow.

Requirements

  • 6+ years in Software/Data Engineering with proven track record deploying ML/AI systems in production.
  • Bachelors degree in an engineering discipline
  • Expertise in Generative AI, LLMs, RAG architectures, and prompt engineering.
  • Expert Python proficiency and modern software architecture (APIs, microservices, Kubernetes).

Nice To Haves

  • Experience with GCP preferred (AWS or comparable cloud platforms acceptable). Palantir Foundry is a plus.
  • Proven ability to lead technical teams and present architectures to executive audiences.
  • Experience with AI Agent frameworks (LangGraph, ADK) and classical ML is a plus.

Responsibilities

  • Lead design and development of enterprise-scale AI systems integrated with broader IT landscape (AWS, GCP, Palantir).
  • Build RAG pipelines and multi-agent systems, driving evolution toward autonomous Agentic AI.
  • Drive AI projects from PoC to production (scaling, CI/CD, MLOps, monitoring).
  • Provide technical leadership, code reviews, and mentorship to internal/external teams.
  • Act as technical advisor bridging business requirements and technical feasibility.
  • Implement AI governance guardrails for data privacy and hallucination prevention.
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