aimlroles

Lead AI and Machine Learning Engineer - Vice President OR Lead AI Engineer, Generative AI - Vice President

Citi Open · verified Oct 20, 2026
Hybrid Pune Maharashtra India Full-time VP Machine Learning Engineering

At a glance

VP-level Machine Learning Engineering role at Citi. Pune Maharashtra India · full-time.

Pay not stated Machine Learning Engineer salary

RoleMachine Learning Engineering
SeniorityVP
LocationPune Maharashtra India
WorkplaceHybrid
EmploymentFull-time
PostedSep 28, 2026 · 3w ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build and deploy agent-based AI and generative AI systems for banking needs, with reliability, security and scale in mind
  • Connect machine learning and language-model services into full-stack applications
  • Prototype new agent and generative AI approaches, then bring useful capabilities into broader solutions
  • Set technical direction through production code, design guidance and architecture checks
  • Move AI work from proofs of concept into cloud-native releases, and measure performance to guide improvements

What you bring

  • You have twelve to fifteen years of hands-on engineering work delivering scalable enterprise systems
  • You bring deep knowledge of agent-based AI, machine learning and advanced software engineering
  • Python is essential, alongside implementation experience with generative AI frameworks such as LangChain, AutoGen or another listed framework
  • You have built language-model solutions with vector databases and retrieval-augmented generation, and have tuned models
  • You have production experience with generative AI operations, plus MLOps lifecycle tooling and Docker

Who this fits

This suits a senior, hands-on engineering lead who can shape technical standards while building and deploying AI systems. The role is based in Pune, India, with a hybrid arrangement. A bachelor’s degree in computer science, mathematics or an equivalent field is required; a master’s degree is preferred.

From the employer

Job Description

We’re currently looking for a high caliber professional to join our team as Vice President, Application Development Tech Lead Analyst (C13) based in Pune, India.

XVA Technology at Citi is undertaking a bold, multi-year transformation to build a best-in-class centralized cross asset platform risk system. We are re-engineering our technology estate to achieve world-leading performance and resiliency, enabling new capabilities. Our ambition is to deliver a seamlessly integrated, highly automated platform that drives outstanding client outcomes and accelerates growth across our global franchise. As part of the team, you'll collaborate closely with high-caliber engineers and deeply engaged business and product partners - working together to define and deliver the next generation of XVA technology at Citi.

Role Overview/What will you do:

As an Applications Development Technology Lead Analyst, you will be instrumental in shaping the future of our product quality and delivery, working towards a target state of a fully automated platform with minimal manual QA intervention. This role specifically requires deep expertise in agentic AI and extensive hands-on experience in Generative AI (GenAI) projects. While a solid foundation in Machine Learning (ML) is beneficial, the successful candidate will be instrumental in architecting and implementing scalable AI frameworks, translating complex ideas into robust, production-ready systems, and contributing to Citi's strategic AI initiatives.

Key Responsibilities:

  • GenAI Solution Development: Hands-on implementation, and deployment of scalable, robust agentic AI frameworks and Generative AI solutions for critical banking use cases, ensuring high performance, reliability, and security.
  • Full-Stack Application Integration: Build full-stack applications that seamlessly integrate state-of-the-art Machine Learning (ML) and Large Language Model (LLM) tools and services into comprehensive AI solutions.
  • AI Advancement & Prototyping: Proactively explore, prototype (Proof of Concept), and integrate the latest advancements in AI, particularly in agent-based systems, autonomous AI, and generative AI technologies.
  • Collaboration: Fostering collaboration with cross-functional teams including AI researchers, data scientists, product managers, and software engineers to integrate and scale AI solutions across Citi’s products and services.
  • Code Development & Standards: Write high-quality production code, drive proof-of-concepts, and validate architectural decisions through implementation. Set technical standards, guide design choices, and raise the bar for the team.
  • Deployment: Take AI-enabled capabilities from early exploration and proof-of-concept through to secure, reliable, and production deployments, focusing on cloud-native, container-first services built to scale for enterprise use.
  • Performance Evaluation: Design and implement rigorous metrics and evaluation strategies for AI system and agent performance, driving continuous optimization and behavioral improvement.

Qualifications:

  • Experience: 12 to 15 years of deep hands-on experience in engineering and executing scalable enterprise solutions.
  • AI Expertise: Deep expertise in AI principles, agent-based systems, machine learning, and advanced software engineering practices.
  • Programming Proficiency: Expert proficiency in Python programming language is essential.
  • GenAI Frameworks: Proven experience in implementing Generative AI use cases using frameworks like LangChain, AutoGen, CrewAI.
  • LLM Implementation: Advanced knowledge in Large Language Models (LLM), with hands-on experience in implementing LLMs using vector databases and Retrieval-Augmented Generation (RAG), as well as tuning models. Ability to perform solution architecture validations for LLMs.
  • ML & NLP: Understanding of machine learning models, experience with Natural Language Processing (NLP) libraries and tools.
  • GenAIOps: Experience in putting Generative AI (GenAI) models into production and providing support to them (GenAIOps).
  • MLOps: Experience using MLOps tools like MLflow for lifecycle management of machine learning models.
  • Containerization: Experience in using Docker to create reproducible and scalable environments.
  • Problem-Solving: Strong analytical and problem-solving skills with an aptitude for math and statistics.
  • Communication: Excellent communication and collaboration skills, with the ability to engage effectively with diverse stakeholders.
  • Self-Motivation: Self-motivated and capable of working independently as well as part of a team in a fast-paced environment.
  • Business knowledge of CVA, XVA, regulatory stress testing is preferred

Education:

• Bachelor’s in Computer Science, Mathematics or equivalent.

• A Master’s degree in preferred

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Job Family Group:

Technology

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Job Family:

Applications Development

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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