Engineer Lead, Artificial Intelligence (Agentic AI, Python, LLM) 8 to 10 Years- Pune/ Bangalore

Overview

Design and build generative artificial intelligence and agent-based solutions across FIS, integrating large language models with enterprise platforms, application programming interfaces and workflows, and evaluating them for accuracy, reliability, safety and grounding.

What you'll do

• Design and build generative artificial intelligence applications using proprietary and open-weight large language models.
• Develop agent-based systems and workflows that support planning, memory, tool use, orchestration, human oversight and autonomous tasks.
• Integrate artificial intelligence solutions with enterprise platforms, application programming interfaces and business workflows.
• Build and deploy representational state transfer services using Flask or FastAPI.
• Evaluate model, agent and system performance, including accuracy, reliability, grounding and safety.

What you'll need

• At least 8-10 years of overall professional experience.
• At least four years working with artificial intelligence, generative artificial intelligence or agent-based artificial intelligence.
• Designing and building GenAI-powered applications using LLMs (open and proprietary).
• Building agent-based systems with planning, memory, tool use, and orchestration.
• Implementing agentic workflows (multi-agent, human-in-the-loop, autonomous tasks).
• Hands-on experience with large language models, prompting techniques, structured outputs, model routing, context management, memory management and retrieval-augmented generation.
• Strong proficiency in Python and experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras or pandas.
• Experience with vector databases, retrieval systems, cloud platforms such as Amazon Web Services, Google Cloud or Microsoft Azure, and services built with Flask or FastAPI.
• Bachelor's degree in engineering or a related field, or an equivalent combination of education, training and work experience.

Nice to have

• Experience fine-tuning large language models, including parameter-efficient approaches such as low-rank adaptation and quantized low-rank adaptation.
• Familiarity with orchestration tools such as LangChain, LlamaIndex, AutoGen or the OpenAI Assistants application programming interface.
• Knowledge of production machine learning operations, continuous integration and delivery, monitoring, observability, security, compliance and data governance.

Details

• Location: Pune, India (source location line: IND PUNE FL7); Bangalore is also named in the title.