Agentic AI Engineer

About the Role

We are seeking a passionate Agentic / Retrieval-Augmented Generation (RAG) AI Engineer to design, build, and optimize intelligent automation systems that integrate large language models (LLMs) with software development life cycle (SDLC) workflows used in avionics and safety-critical software projects .

You will develop autonomous AI agents, RAG pipelines, and reasoning systems that streamline documentation, verification, and compliance processes in line with aerospace standards.

Key Responsibilities

• Design and implement RAG pipelines integrating LLMs with vector databases and retrieval systems to support traceability, requirements validation, and code-document alignment.
• Develop autonomous AI agents capable of multi-step reasoning, task execution, and contextual decision-making across software lifecycle phases (requirements, design, code, test, verification).
• Fine-tune and evaluate LLMs and embeddings for domain-specific avionics use cases and engineering documentation.
• Integrate APIs and frameworks such as OpenAI, Anthropic, LangChain, and LlamaIndex into AI-driven SDLC automation workflows.
• Work with vector databases (e.g., Pinecone, Chroma, Weaviate, Milvus) for efficient retrieval and knowledge management.
• Implement context and memory management systems enabling agents to maintain state and learn from interactions.
• Collaborate with avionics domain experts and cross-functional teams (ML, backend, and verification engineers) to deploy scalable and compliant AI solutions.
• Monitor, evaluate, and optimize agent performance for accuracy, latency, cost, and reliability.
• Stay current with advancements in LLMs, RAG architectures, and AI agents, applying best practices to regulated software domains.

Desirable Skills & Domain Knowledge

Preferred Technical Stack

Qualifications