Senior AI Engineer

Overview

Implement and deploy enterprise Generative AI and agentic solutions within the Data Science function, as a hands-on individual contributor working under senior engineers (approximately 90% execution, 10% strategy).

What you'll do

• Implement and deploy GenAI features and models, including data preparation, prompt engineering, agent/workflow building, testing and performance tuning, within established engineering patterns.
• Solve well-defined to moderately complex problems, applying proven tools and techniques and escalating novel or architectural challenges to senior engineers.
• Contribute to GenAI components (LLMs, RAG, agentic workflows, context engineering) and support their integration across data, models and applications.
• Support disciplined evaluation and error analysis of AI outputs to help keep non-deterministic systems predictable and reliable.
• Debug, monitor and tune deployed solutions to meet quality, latency and cost expectations.
• Collaborate day-to-day with fellow AI engineers, AI architects, data scientists, data engineers, data architects, data stewards, developers and QA, working with the team lead and senior engineers and interacting occasionally with product owners.
• Work within established guidelines and processes, take ownership of assigned deliverables, and flag risks and dependencies early.
• Build tools and capabilities that generate value across the business, providing indirect, advisory impact to outcomes.

What you'll need

• Bachelor's degree in Computer Science, Engineering, Information Technology or a related field.
• 4-5 years of experience in AI/ML, data science or software engineering, with hands-on model development and some production deployment.
• Working expertise with LLMs, RAG, prompt and context engineering, and agentic workflows / frameworks (e.g., LangGraph), grounded in evals and error analysis.
• Familiarity building and deploying solutions on a major cloud platform, preferably Microsoft Azure.
• Solid programming skills (e.g., Python) and good software-engineering practices in coding, testing and integration.
• Strong problem-solving skills and attention to detail, applying established patterns and seeking guidance when needed.
• Collaborative team player with clear communication skills.

Nice to have

• Microsoft Certified Azure AI Engineer Associate.
• Building GenAI features within a business unit or function (Data Science / IT).
• Familiarity with the modern data and AI stack (e.g., Azure AI / OpenAI services, Snowflake).
• Awareness of Responsible AI, security and privacy considerations.

Details

• Location: Bengaluru - Brookfield GCC.