AI Engineer

Overview

Design and develop autonomous AI agents and multi-agent systems on Airbus's Engineering Knowledge Framework (EKF) AI platform. Translate business logic and engineering workflows into secure, compliant AI solutions supporting digital continuity and AI-augmented aircraft engineering.

What you'll do

• Understand complex business and engineering workflows, identify augmentation opportunities, and document functional requirements for AI agent personas, tools, and guardrails.
• Evaluate AI automation suitability, analyze engineering requirements, and identify failure modes, data gaps, and regulatory risks before development.
• Design, configure, and fine-tune AI agents, prompting strategies, and agent bodies of knowledge within the internal EKF platform.
• Act as the primary liaison between engineering business teams and EKF development teams, managing expectations and aligning on agent capabilities and limitations.
• Collaborate with EKF development teams to refine, clarify, and prioritize user stories for EKF capabilities, agent tools, APIs, and data pipelines.
• Develop AI behavior test plans covering accuracy, hallucination mitigation, and regression testing.
• Lead User Acceptance Testing (UAT) and ensure agents meet quality and safety standards.
• Create agent specifications, prompt catalogs, and configuration guides.
• Train end-users on interacting with and auditing AI agents.
• Monitor production agent performance, analyze user feedback loops, and improve agent reasoning, context retrieval, and efficiency.

What you'll need

• 5+ years of progressive experience as a Business Analyst, Systems Designer, or Solution Architect.
• A minimum of 2 years explicitly focused on designing decision support systems, AI agents, or advanced LLM implementations.
• Ability to quickly learn and master internal, proprietary agent-building platforms and orchestration frameworks with provided training.
• Strong understanding of LLM capabilities, agentic design patterns such as reflection, planning, and tool-use, RAG patterns, semantic data handling, and LLM as judge.
• Solid understanding of databases, knowledge graphs, vector embeddings, and API integrations required to grant agents access to external tools.
• Excellent requirements elicitation, analysis, and documentation skills, including use cases, user stories, interaction diagrams, and process flows.
• Proven ability to balance technical ideals with operational reality and prioritize reliability, maintainability, and data quality over theoretical AI performance.
• Outstanding communication, presentation, and interpersonal skills.
• Proven ability to translate complex business logic into AI instructions and constraints.
• Well-experienced in Agile/SAFe methodologies and modern project management tools such as VersionOne, ALM, Jira, and Confluence.
• Autonomy, strong leadership, and influence skills to drive collaboration across interfacing technical and Airbus engineering business teams in a fast-paced environment.

Nice to have

• Experience in the aerospace engineering field.

Details

• Location: Bangalore Area.
• Employment type: Permanent.