You will be involved in understanding the AI application in the digital solutions and enablers that we are building for usage by global Airbus teams. You will be expected to develop and use existing models that can fast track and enable us in optimizing our transformation and migration activities like Oracle to Postgres, .NET migration activities, MS decommissioning and movement to google suite to mention a few.

Responsibilities

Build and optimize Generative AI workflows using Python and LangChain.
Lead and execute Microsoft platform decommissioning activities, including assessment, planning, migration, and retirement of legacy systems, while ensuring minimal disruption to business operations and adherence to compliance and security standards.
Drive and support the .NET Sunset Program by assessing legacy applications, planning and executing migration or decommissioning strategies, coordinating with cross-functional teams, and ensuring seamless transition to modern, scalable technologies.
Develop and refine prompt templates for effective interaction with LLMs.
Integrate tools and agents within the LangChain ecosystem to handle real-world tasks.
Implement RAG pipelines using vector databases to enhance response quality.
Work closely with architects to understand requirements and translate them into functional implementations.
Collaborate with the AI/ML team to build interactive frontends using Streamlit or Gradio.
Assist in deploying and testing models and services on GCP cloud infrastructure.
Document work, share learnings, and actively participate in brainstorming sessions.
Any new activities which has a need to use AI to complete it in an optimal way

Required Technical Expertise:

Python
Machine Learning Frameworks like Tensorflow/PyTorch
Network Graph Visualization techniques
Compressible Flow Aerodynamics

Must Have

Strong knowledge and hands-on experience with Python programming.
Experience working with Generative AI workflows using LangChain.
Familiarity with LangChain Prompt Templates and LangChain Agent tools.
Understanding of Retrieval-Augmented Generation (RAG) techniques.
Experience working with Vector Databases (e.g., FAISS, Chroma, Pinecone, etc.).
Proficiency in using Jupyter Notebooks for experimentation and prototyping.
Experience working on real-time projects with a proper project structure using IDEs like VS Code or PyCharm.
Strong critical thinking and problem-solving skills.
Good communication and collaboration abilities.

Nice to Have

Hands-on experience with Streamlit or Gradio for building AI frontends.
Basic understanding of Google Cloud Platform (GCP) services.
Exposure to APIs and tool integrations in AI applications.
Previous project or coursework in LLM-based or NLP-driven applications.

Area:

AI / ML Engineering for building Digital Solutions and Enablers

Education:

Engg. background with exposure to Machine Learning Deep Learning, Artificial Intelligence

Soft skills:

Ability to work independently in a transnational team.
Good communication and interpersonal skills.
Flexibility Adaptability

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