Senior Lead AI Engineer

About the Role

We are looking for a Senior lead Engineer, Applied AI who thrives at the intersection of cutting-edge trends in different modalities of Artificial Intelligence (AI) and real-world impact in various business units of Collins Aerospace. In this role, you’ll transform various innovations in AI, including but not limited to Generative AI or Agentic workflows, into production-grade applications that deliver measurable business and operational value.

You’ll work across the full development cycle—from experimenting with state-of-the-art AI techniques to deploying applications and frequently demoing to stakeholders via incremental demoes. This is a highly hands-on position where you’ll design, build, and own the systems you create, ensuring that each deliverable is both technically robust and value-validated in production.

End-to-End Ownership: Lead the full lifecycle of AI feature development from research, prototyping to production and continuous improvement with feedback from stakeholders for value extraction.

Applied AI driven solution/pipeline development: Design, develop, and operationalize applications that leverage diverse modalities such as text, vision, and structured data by applying various techniques and utilize frameworks that support developing identified techniques.

Rapid Prototyping to Production: Develop iterative prototypes to validate AI concepts and regularly demo them to stakeholders via moving the prototype to production, gather feedback and translate the work into measurable value uplift with continuous improvements.

System Integration: Engineer reliable back-end and front-end services and integrate solution with enterprise services for cyber and legal compliance.

Automation & MLOps: Implement experiment tracking, model versioning, and CI/CD pipelines for seamless progression from experiments to stable releases.

Cross-functional Value Delivery: Collaborate with product teams, research teams and domain experts to identify high-impact use cases where AI can deliver tangible improvements, quantify ROI, and communicate results effectively.

Programming: Strong proficiency in any of the object oriented programming languages for building modular systems, combined with advanced Python skills for developing applied AI applications and data pipelines, and backend services using frameworks like PyTorch, FastAPI, Langchain, LangGraph etc..,

Generative AI (LLMs and Multi Modal expertise): Experience with enterprise and open source frontier models such as GPT, Claude, Gemini, Llama, or Mistral for custom agent or knowledge extraction workflows.

Infrastructure: Hands-on with Docker, Kubernetes, GitLab CI/CD, and GPU-accelerated environments.

Data Stack: Practical understanding of anyone RDMS such as PostgreSQL, vector databases, and efficient data preprocessing pipelines.

System Mindset: Proven record of taking prototypes to production and ensuring long-term maintainability and observability.

Bachelors /master's degree with 6-9 yrs of experience building LLM-centric agents, enterprise copilots, or RAG-based applications.

Familiarity with LangGraph, Semantic Kernel, or any emerging frameworks.

Background in evaluation frameworks for LLM performance and value benchmarking.

Domain experience in Aerospace, Autonomous Systems, or Engineering Analytics.

Strong portfolio of deployed AI projects or open-source contributions.

Familiarity with core Computer vision and Natural Language Processing techniques.

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