State Street

Generative AI Intern

InternshipWork from HomeBengaluru, Karnataka3 months41K/mo2 openingsImmediate / Rolling

About this internship

Start your career in generative AI with State Street as a Generative AI Intern in Bengaluru. You will sit with a working team, use the same tools and systems they do, and own a defined piece of work from day one. About the role As a Generative AI Intern at State Street, your core focus will be…

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Skills you'll use

PythonLarge Language ModelsPrompt EngineeringLangChainHugging Face TransformersRAG PipelinesVector DatabasesPyTorchREST APIsModel Evaluation

What you'll do

Work on building, prompting and evaluating LLM-powered features alongside the core team
Apply Python, Large Language Models, Prompt Engineering, LangChain to live, production-facing problems
Document your work clearly for reviewers and stakeholders
Participate in reviews and act on the feedback you receive
Collaborate across engineering, product, design or business as required
Follow the team's quality, testing and documentation standards

Who can apply

Pursuing or recently completed B.E./B.Tech/BCA/MCA/M.Sc (CS, AI, Data Science) — 2026 freshers & final-year students welcome
Working knowledge of Python, Large Language Models, Prompt Engineering (or a genuine willingness to learn them)
Strong fundamentals in your discipline and clear problem-solving ability
Care with detail and the discipline to document your work
Clear written and verbal communication in English
Based in or willing to work from Bengaluru, Karnataka

Perks & benefits

Letter of RecommendationMentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunity

Interview & selection process

2 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Team-fit / behavioural interview with the team

About State Street

State Street operates in the financial services sector and has an active presence in Bengaluru. Interns here are put on real work from the start, because the team's view is that the fastest way to learn a craft is to practise it under people who already do it well — not to watch it from a…

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