Description :

Job Summary :

Drive cutting-edge research and development in autonomous AI agents, Agentic AI, and GenAI systems to power next-gen airline solutions.

Key Responsibilities :

- Design, develop, and deploy autonomous AI agents using Agentic AI frameworks.

- Build and optimize multi-agent collaboration protocols (MCP, A2A) for scalable decision-making systems.

- Fine-tune large language models (LLMs) for domain-specific airline use cases.

- Architect and implement GenAI solutions for operational and customer-facing applications.

- Conduct experiments and benchmarking for model performance and reliability.

- Collaborate with engineering teams to integrate AI models into cloud-native environments (Azure/GCP).

- Publish findings, contribute to patents, and represent the lab in external forums and conferences.

Required Skills / Must-Have :

- Technical Skills : Python, PyTorch/TensorFlow, LangChain, FastAPI, Azure ML or Vertex AI, Docker/Kubernetes.

- AI/ML Expertise : Autonomous agents, Agentic AI, LLM fine-tuning, GenAI pipelines.

- Protocols : MCP (Multi-agent Collaboration Protocol), A2A (Agent-to-Agent Communication).

- Cloud Platforms : Azure or GCP (hands-on experience).

- Experience : 2 to 5 years in applied AI/ML, preferably in innovation or R&D settings.

Nice-to-Have / Preferred Skills :

- Experience with airline industry datasets or operational systems.

- Familiarity with Reinforcement Learning (RL) and multi-agent systems.

- Knowledge of MLOps practices and CI/CD for ML workflows.

- Contributions to open-source AI projects or publications in top-tier conferences.

Education & Qualifications :

- Primary : Bachelors in Engineering or Mathematics with strong AI/ML experience.

- Secondary : Masters or PhD in Computer Science, AI/ML, Data Science, or related field.

Certifications/Licenses :

- Preferred : Azure AI Engineer Associate, Google Cloud ML Engineer, TensorFlow Developer Certificate.

Skills Grouping & Synonyms :

- AI/ML : Autonomous agents / Agentic AI / multi-agent systems / GenAI / LLM fine-tuning.

- Cloud : Azure ML / GCP Vertex AI / cloud-native ML / MLOps.

Protocols : MCP / multi-agent collaboration / A2A / agent communication.

Development : Python / FastAPI / LangChain / PyTorch / TensorFlow.