Description

Architect, fine-tune, and deploy Large Language Models and Generative AI solutions to enhance business applications.

This role is on-site.

Responsibilities

• Design and implement RAG architectures, prompt engineering, and model optimization strategies using LLMs like GPT-4 and Llama.
• Build and maintain scalable ML pipelines and GPU-based inference systems in AWS, GCP, or Azure.
• Translate business requirements into technical specifications and manage project scope, timelines, and deliverables.
• Guide offshore technical teams and coordinate project execution to ensure high-quality, safe, and efficient outputs.
• Present technical trade-offs and performance results to non-technical stakeholders and leadership.

Required Skills

• 10+ years of ML engineering experience, including 1-2 years dedicated to Generative AI or NLP.
• Strong proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
• Hands-on experience with LLMs, RAG, LangChain, Vector Databases, Knowledge Graphs, and Agentic AI.
• Experience with cloud platforms (AWS/GCP/Azure) and tools like AWS SageMaker, Bedrock, S3, Lambda, and Glue.
• Familiarity with MLOps/LLMOps, including Docker, Kubernetes, and CI/CD tools.
• Proficiency with IDEs such as Cursor, AWS Kiro, and GitHub Copilot.
• Excellent verbal and written communication skills with the ability to articulate complex concepts simply.

Preferred Skills

• Engineering degree in Computer Science or equivalent, with relevant Machine Learning certification.
• Experience in the banking, financial services, or payments industry.

Key Skills

Education

Any Graduate