Job Role: Senior Gen AI Engineer – GenAI & Advanced ML
Job Type: Full-time
Experience: 4–7 years
About the Role
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 SageMaker) is mandatory.
If you enjoy owning GenAI strategy end‑to‑end and building scalable AI systems, this role is for you.
Key Responsibilities
- Architect end‑to‑end GenAI systems including data pipelines, training, evaluation, deployment, and monitoring.
- Drive initiatives across:
- LLM‑based applications
- Retrieval‑Augmented Generation (RAG)
- AI agents & orchestration workflows
- Build and deploy GenAI solutions on AWS Bedrock and SageMaker .
- 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.
Qualifications & Skills
- 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
- Fine‑tuning & inference optimization
- AI agents / orchestration
- AWS (Mandatory):
- Amazon Bedrock
- Amazon SageMaker
- Experience deploying AI/ML solutions on AWS
- Proficiency in Python (pandas, NumPy, scikit‑learn, PyTorch/TensorFlow).
- SQL and large‑scale data processing experience.
- Strong understanding of ML system design and model evaluation.
- Excellent communication and stakeholder management skills.
Preferred Qualifications
- Experience with Spark / big data ecosystems.
- Knowledge of vector databases (FAISS, Pinecone, Weaviate).
- Exposure to AI governance and responsible AI frameworks.