Lead AI Solutions Systems Engineer

Airbus Digital is looking for a Lead AI Solutions Systems Engineer to join the team. This role can be based in Herndon, VA, Atlanta, GA, Sunnyvale, CA or Mobile, AL. The Lead AI Solutions Systems Engineer is the lead technical architect and solution designer in the North America AI and Advanced analytics Product Service Line. This role will support the Head of digital AI and Advanced analytics to drive the technical strategy, data modeling, and high-level solution design from proof-of-concept (PoC) to industrialization. As a Lead AI Solutions Systems Engineer, you will act as a deeply technical, hands-on, and business-facing lead architect and builder.

Responsibilities

Evaluate the technical feasibility, data readiness, and infrastructural viability of proposed AI initiatives; Act as the principal technical translator, formalizing complex business problems into mathematical, data engineering, and algorithmic requirements; Define and design technical validation metrics, including ML quality, precision, recall, system latency, data bias, drift, and LLM safety/alignment safeguards; Act as a trusted advisor to business leaders; Accompany business throughout PoCs and their industrialization, from opportunity framing to production hand-over; Design solution blueprints, evaluate build-vs-buy trade-offs, and design staging plans; Collaborate with the AI Lead Developer to define local software development guidelines, API schemas, and MLOps release pipelines; Lead and frame assistant/agent coding practices across the team and its delivery partners; Rapidly prototype initial Proof of Concepts (PoCs), establish development sandboxes, and actively co-author code alongside delivery partners; Support the technical maturity ramp-up of the team; Architect the late-2026 transition to Gemini Enterprise, designing migration paths from custom-coded frameworks to robust no-code agentic structures; Coordinate technically with European technical teams (AgentAiR) to align local implementations with global enterprise architectures, API standards, and corporate data governance frameworks; Other duties as assigned

Requirements

Master's degree in AI (ML / Data Science), Computer Science, or a highly quantitative field; Minimum of 10 years of experience in advanced analytics initiatives, including mandatory hands-on, production-grade architecture and engineering experience in AI, and at least one Generative AI / Agentic AI system successfully designed, prototyped, and integrated into a production environment; Significant experience across several business branches—Corporate (e.g., HR, Finance, Facilities) AND Operations (e.g., Procurement, Supply Chain, Logistics) at a minimum; Proven technical leadership in designing and delivering production-ready system architectures, with experience in database modeling and implementing microservices; Proven ability to shape both technical solutions and software architectures (frontend, backend, AI components); Robust experience in data modeling and/or data engineering, showing a deep understanding of business ontologies, physical data models, and modern data practices; Proven ability to frame complex business problems with non-technical stakeholders, translating complex business problems into clear, production-ready technical specifications and data requirements; Experience working in an innovation cell or startup environment, combined with experience in a large, matrixed global enterprise; Authorized to Work in the US; Technical and Scientific Rigor: mastery of mathematical, statistical, and algorithmic foundations of AI; Software Engineering Blueprinting: deep practical expertise in SDLC, API contract design, containerization (Docker, Kubernetes), regression testing, and deployment pipelines; Value-Driven Mindset: prioritizes real-world business outcomes and ROI over algorithmic sophistication; Open-Mindedness: willingness to revisit established solutions when new, cheaper, or more efficient options emerge; Organizational Tolerance: comfortable navigating complex global corporate structures, data governance constraints, and dependencies tied to Europe-led solution deployments; Active Listening, Influence and Collaboration, Coaching and Delegation; Technical Systems Proficiency: Advanced Analytics and ML Platform (SciKit and/or MLlib (PySpark), PyTorch, TensorFlow), Generative and Agentic AI Stack (Python/Langgraph or ADK, RAG), DevOps and Cloud (Streamlit/React, PostgreSQL/Firebase/BigQuery, GCP Cloud Run, Python backend), AI-Assisted Coding Tools (Gemini CLI, Claude Code, Codex); Travel Required: 10%

Nice to have

Specialization in NLP, Generative AI, or Agentic AI; Manufacturing experience highly preferred; Experience in agent coding, or in framing and supporting an assistant / agent coding practice; Fluent in French is a plus; Working familiarity with Palantir Foundry / Skywise; Hands-on experience optimizing LLM models using Vertex AI Studio on GCP; Experience in NLP and graph Knowledge: Named entities, Spacy, FlairNLP, LLM-Wiki / Hierarchical RAG, Neo4j, Spanner, GKG; Experience in supporting teams to migrate from Github Copilot to Gemini CLI

Benefits

Relocation assistance for qualified positions; Comprehensive compensation and benefits package