Senior Gen AI Engineer

Job Role:

Senior Gen AI Engineer – GenAI & Advanced ML

Location:

Mumbai/Pune

Job Type: Full-time

Experience:

4–7 years

We are looking for a Senior AI Engineer – Generative AI with leadership experience and deep expertise in AI/ML and production‑grade GenAI systems. This role requires a hands‑on technical leader who has built, deployed, and scaled Generative AI solutions while leading teams and driving architectural decisions.

The ideal candidate will have a strong foundation in machine learning, deep learning, and statistical modeling, along with real‑world experience in LLMs, RAG, fine‑tuning, and AI agents. A background in forecasting or predictive modeling should complement broader AI/ML problem‑solving.

Strong hands‑on experience with AWS (especially Bedrock and Sage Maker) is mandatory.

If you enjoy owning GenAI strategy end‑to‑end and building scalable AI systems, this role is for you.

• Architect end‑to‑end GenAI systems including data pipelines, training, evaluation, deployment, and monitoring.
• Drive initiatives across LLM‑based applications, Retrieval‑Augmented Generation (RAG), prompt engineering & optimization, fine‑tuning & model adaptation, AI agents & orchestration workflows.
• Build and deploy GenAI solutions on AWS Bedrock and Sage Maker.
• Apply ML/DL techniques for forecasting, prediction, and intelligent automation.
• Lead and mentor AI engineers and data scientists.
• Collaborate with product and business stakeholders to deliver scalable AI solutions.
• Design and maintain ML/GenAI pipelines for experimentation and retraining.
• Ensure responsible AI, scalability, and performance standards.

• 4–7 years of experience in AI/ML, Data Science, or AI Engineering.
• Strong foundation in Machine Learning, Deep Learning, and Statistical Modeling.
• Generative AI (Hands‑on): LLMs and foundation models, prompt engineering, RAG pipelines & vector databases, fine‑tuning & inference optimization, AI agents / orchestration.
• AWS (Mandatory):
  Amazon Bedrock, Amazon Sage Maker, experience deploying AI/ML solutions on AWS.
• Proficiency in Python (pandas, Num Py, scikit‑learn, PyTorch/Tensor Flow).
• SQL and large‑scale data processing experience.
• Strong understanding of ML system design and model evaluation.
• Excellent communication and stakeholder management skills.

• MLOps practices (CI/CD, monitoring, versioning).
• Experience with Spark / big data ecosystems.
• Knowledge of vector databases (FAISS, Pinecone, Weaviate).
• Exposure to AI governance and responsible AI frameworks.