Role Purpose

Support the Digital & AI Centre of Excellence by helping convert business requirements into practical AI proof-of-concepts and delivery-ready solution components. The role is intended for a fresher or early-career engineer who can learn quickly, use AI-enabled coding platforms responsibly, and work with focus and discipline from experiment to production handoff.

This is a hands-on builder role, not a research-only role. The expectation is to understand the problem, build a working first version, test it with users, document what works and what does not, and support senior engineers in moving successful ideas toward secure, maintainable production use.

Core Expectations

- Understand requirements and shape practical AI POCs
- Work with business and product teams to understand workflows, pain points, data availability and expected outcomes. - Break ambiguous requests into clear problem statements, assumptions, success criteria and a first POC approach. - Build quick prototypes using approved AI tools, APIs, prompts, retrieval patterns, workflow agents or simple interfaces. - Test early with users and capture feedback, limitations, risks and next steps clearly.
- Execute with engineering discipline
- Write clean, understandable code with proper use of Source control - Use AI-assisted and agentic coding platforms productively while reviewing, debugging and owning the final output. - Create small test sets, compare outputs, identify failure cases and improve prompts, retrieval logic or code iteratively. - Maintain clear notes on decisions, dependencies, assumptions,



known issues and handover requirements.
- Support movement from POC to production
- Help convert promising POCs into reusable components, APIs, prompts, evaluation checks or workflow nodes. - Work with senior engineers and technology teams on integration, deployment support, monitoring needs and production handoff. - Follow approved platform, security, privacy and responsible AI guardrails while handling data and tools. - Keep solutions simple, modular and maintainable so they can be scaled or reused across business workflows.

Required Experience

- Fresh graduate or candidate with experience in software engineering, AI/ML, data science or related project work. - Bachelor degree in Computer Science, Engineering, IT, Data Science, AI/ML, Mathematics, Statistics or a related field. - Academic project, internship, hackathon, GitHub portfolio or capstone work involving AI, automation, data, APIs or application development will be preferred. - Prior enterprise experience is not mandatory; learning ability, curiosity, discipline and execution focus are valued.

Required Skills

- Strong Python fundamentals (or any coding language of choice), basic debugging, clean coding habits,



Git/Bitbucket usage and comfort working with libraries. - Basic understanding of SQL, data cleaning, APIs, JSON and structured or unstructured data handling. - Awareness of GenAI concepts such as prompts, embeddings, RAG, structured outputs, tool calling and hallucination risks. - Comfort using AI-enabled coding and productivity tools responsibly to accelerate development and research. - Ability to document work clearly enough for review, reuse and handover. - Natural curiosity, persistence, ownership mindset and ability to stay focused through iterations.

Good to Have

- Exposure to LangChain, LlamaIndex, LangGraph, CrewAI, n8n or similar agent/workflow tools. - Basic familiarity with vector databases, document processing, cloud services, Docker, CI/CD, logs or monitoring. - Interest in building productivity tools, automation utilities and user-facing AI assistants that teams actually adopt.

Role Success Measures

- Business requirements are converted into explicit POC plans with success criteria and practical delivery steps. - POCs are built quickly, tested honestly and documented with limitations, risks and recommendations. - Reusable code, prompts, workflows and evaluation checks are created instead of one-off demos wherever possible. - Successful POCs move more smoothly toward production handoff with clearer engineering, security and support inputs. - The engineer shows strong learning velocity, disciplined follow-through and responsible use of AI-enabled tools.

📌 Intern - AI Engineering (Mumbai)
🏢 Nuvama Group
📍 Mumbai