Description

You will design, build, and deploy production-grade Generative AI and LLM systems for complex enterprise business problems.

This role is on-site.

Responsibilities

• Build and operate end-to-end ML and Generative AI services with a focus on scalability.
• Implement multi-modal RAG systems and Agentic AI architectures for enterprise solutions.
• Fine-tune and evaluate generative models (e.g., GPT-4.1) for NLP use cases including summarization and text generation.
• Establish MLOps capabilities with automated pipelines, monitoring, and model lifecycle management.
• Mentor junior engineers through design and code reviews while communicating technical results to stakeholders.

Required Skills

• 15+ years of experience in software or ML engineering.
• Strong proficiency in Python, R, or Java.
• Experience developing multi-modal RAG systems and Agentic Design patterns.
• Hands-on expertise with TensorFlow, PyTorch, Scikit-learn, and OpenAI API.
• Cloud platform experience: AWS, Azure, Google Cloud Platform, Snowflake, or Databricks.
• Containerization skills with Docker and Kubernetes; familiarity with microservices architecture.
• Understanding of statistics, deep learning, GANs, VAEs, and reinforcement learning.

Preferred Skills

• Expertise in RAG pipeline design and advanced prompting strategies (Chain-of-Thought, Tree-of-Thoughts, Graph-of-Thoughts).
• Familiarity with the financial services industry.
• Experience with DevOps practices and Agile methodologies.

Key Skills

Education

Bachelor's degree