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Senior AI and Machine Learning Engineer - Assistant Vice President

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Time Type: Full time------------------------------------------------------ Most Relevant Skills
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting

What you’ll work on

Full posting
  • Implement and deploy scalable agentic AI and generative AI solutions for banking use cases

  • Build full-stack applications that integrate ML and LLM tools and services

  • Prototype and integrate new AI advances, especially agent-based and autonomous systems

  • Design metrics and evaluation strategies for AI system and agent performance

  • Take AI capabilities from proof of concept to secure, cloud-native production services

From the employer’s posting
Hands-on implementation, and deployment of scalable, robust agentic AI frameworks and Generative AI solutions for critical banking use cases
Build full-stack applications that seamlessly integrate state-of-the-art Machine Learning (ML) and Large Language Model (LLM) tools and services
Proactively explore, prototype (Proof of Concept), and integrate the latest advancements in AI, particularly in agent-based systems, autonomous AI, and generative AI technologies.
Design and implement rigorous metrics and evaluation strategies for AI system and agent performance
Take AI-enabled capabilities from early exploration and proof-of-concept through to secure, reliable, and production deployments

What you’ll bring

All qualifications

Core experience

  • Experience: 7+ years of deep hands-on experience in engineering and executing scalable enterprise solutions.
  • Bachelor’s in Computer Science, Mathematics or equivalent.
  • Ability to perform solution architecture validations for LLMs.
  • Communication: Excellent communication and collaboration skills, with the ability to engage effectively with diverse stakeholders.
Qualification wording
Experience: 7+ years of deep hands-on experience in engineering and executing scalable enterprise solutions.
Bachelor’s in Computer Science, Mathematics or equivalent.
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.
Communication: Excellent communication and collaboration skills, with the ability to engage effectively with diverse stakeholders.
Education & alternatives
Education: • Bachelor’s in Computer Science, Mathematics or equivalent. • A Master’s degree in preferred
• Bachelor’s in Computer Science, Mathematics or equivalent. • A Master’s degree in preferred ------------------------------------------------------
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Posting record

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Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 3, 20264 days ago
Recorded sightings
4
Last seen by us
Nov 7, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 4

Early. Similar jobs usually come down between day 7 and day 71.

At Citi, jobs usually come down by about day 16.

From 4,668 similar postings that came down, and 1,277 of Citi’s. Coming down is not always a hire.

Citi is hiring

162 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
  • 5% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Docker
Where the posting names them
- 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, LangGraph, ADK.
- GenAIOps: Experience in putting Generative AI (GenAI) models into production and providing support to them (GenAIOps). - 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.

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About Citi

People
About 226,000 in 2025.Annual report (SEC Form 10-K)
Company
Listed as C.
H-1B visas
1 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 624, the most 1,094, and the latest week had 868.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

The Olympus Data Reconciliation and Engineering team is responsible for delivering enterprise solutions and common operating model, which provides scalable, efficient and standardise processing for complex reconciliations in the global processing hubs. We are looking for a candidate who can analyze substantial amounts of raw information to find patterns and build AI/ML models. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.

 

This role will be responsible for all aspects of Reconciliation platform design and development and the delivery and adoption of our next generation solution.

 

Key Responsibilities:

As part of the Global Reconciliation Utility (GRU) and Data Engineering team, this role will be responsible for development and implementation of GRU AI ML models strategies.

 

  • 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: 7+ 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, LangGraph, ADK.
  • 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).
  • 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.

 

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:

Data Science

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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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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

 

If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.

View Citi’s EEO Policy Statement and the Know Your Rights poster.

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Chennai, TN, IN

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