Lead Analyst - IT-AI Full Stack Engineer

What you’ll do:

This position is for an AI Developer in the Product Engineering R&D value stream, focused on designing and developing scalable AI-enabled solutions for global business users. The candidate will build Generative AI applications, Agentic AI workflows, AI assistants, automation agents, and intelligent enterprise solutions aligned to business requirements.

Key responsibilities include developing AI/ML pipelines, RAG-based solutions, vector database integrations, LLM-powered applications, autonomous agents, orchestration workflows, APIs, and enterprise system integrations. The candidate will create and manage capabilities such as chatbots, knowledge assistants, document summarization, semantic search, content generation, code assistance, task planning, tool usage, multi-step reasoning, autonomous execution, and human-in-the-loop workflows.

The role requires collaboration with Data Engineering, Cloud, DevOps, Cybersecurity, Enterprise Architecture, IT, and business stakeholders to translate business challenges into practical AI solutions. The candidate will also support model evaluation, prompt engineering, performance tuning, responsible AI practices, deployment validation, documentation, automation opportunities, and continuous innovation in Generative AI, Agentic AI, Machine Learning, and intelligent automation.

Key responsibilities include:

Design, develop, and maintain AI/ML models and solutions to address business needs.

Collaborate with stakeholders to translate requirements into AI-driven applications and data pipelines.

Manage AI infrastructure, including model training, deployment, and runtime environments.

Monitor model performance, system health, and resource utilization to ensure reliability and SLA compliance.

Troubleshoot AI systems, perform root cause analysis, and drive continuous improvements.

Support end-to-end AI lifecycle across Dev, Test, UAT, and Production with CI/CD and versioning practices.

Enforce security, access control, data privacy, and compliance standards for AI systems and datasets.

Qualifications:

Bachelor’s degree in computer science, engineering, or related field. A master’s degree in AI, Machine Learning, or Data Science is preferred.

8-12 years of total experience with 4+ years of development experience in AI / ML / Intelligent Automation Domain

Skills:

Exposure to widely used AI/ML frameworks and platforms with a strong understanding of model architectures and deployment patterns

Strong programming experience with widely used languages in AI / MLOps domain, such as, Python, SQL, Java etc

Knowledge of data engineering and AI workflows, including integration with data sources, APIs, and enterprise systems (minimum 4 years preferred)

Experience in data modeling, feature engineering, and working with structured/unstructured datasets (experience with visualization or analytical tools is a plus)

Good understanding of AI/ML infrastructure, including cloud platforms, containers, and model serving frameworks

Basic understanding with networking concepts (APIs, endpoints, ports, security layers) relevant to deploying and consuming AI services

Experience in customizing or fine-tuning models (e.g., LLM fine-tuning, prompt engineering) is an advantage

Good understanding of MLOps/AI lifecycle processes, including model training, validation, monitoring, and retraining

Knowledge of change management workflows in AI systems, including version control, model updates, and experiment tracking

Good understanding of DevOps concepts

Good understanding of Cloud Concepts, preferably Azure

Good understanding of ITSM processes

Strong troubleshooting and problem-solving skills

Good communication skills

Good learning agility

Good collaboration & coordination skills