Senior Vice President - AI Lead Engineer - Banking Technology

Citi · Pune · 10+ yrs experience · Posted 2026-07-18

Tech stack: Angular, Django, Docker, FastAPI, Flask, Java, Kubernetes, MongoDB, Next.js, Node.js, Python, React, Spring Boot, TypeScript

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About the role

Role Citi's Banking Technology organization is seeking an exceptional full stack hands-on AI Engineer to lead the design, development, and deployment of cutting-edge AI solutions for the banking sector. This pivotal role involves architecting and implementing a scalable agentic AI framework, translating complex ideas into robust, production-ready systems, and driving tangible business value within Citi. The ideal candidate will be a hands-on technical leader with deep expertise in AI principles, agent-based systems, machine learning, and advanced software engineering practices.
Responsibilities: - Spearhead the end-to-end design, 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.
- Build full-stack applications that seamlessly integrate state-of-the-art ML/LLM tools and services into comprehensive AI solutions.
- Champion an MVP-first approach, focusing on rapid iterations, hypothesis testing, and A/B experiments to achieve continuous improvement and quick "time to value."
- Design and implement rigorous metrics and evaluation strategies for AI system and agent performance
- driving continuous optimization and behavioral improvement.
- Proactively explore, prototype (POC), and integrate the latest advancements in AI, particularly in agent-based systems, autonomous AI, and generative AI technologies.
- Provide hands-on technical leadership, guiding architectural decisions, and 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.
- Exhibit excellent communication and collaboration skills, effectively engaging with diverse stakeholders.
Qualifications: - Deep hands-on experience in engineering and executing scalable enterprise solutions.
- Expert-level proficiency in Python (e.g., FastAPI, Django, Flask, PySpark)
- Solid understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems.
- Hands-on experience with relevant frameworks (e.g., Google ADK, LanGraph, LangChain, AutoGen, CrewAI, N8N).
- Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and relevant libraries (e.g., Scikit-Learn, NumPy, Pandas).
- Proven experience in creating, deploying, and integrating
- MCPs (Model Context Protocol)
- into agentic AI systems.
- Deep familiarity with large language models (LLMs) such as ChatGPT, Claude, Gemini, and Llama, including their application within agentic systems.
- Demonstrated experience in designing and implementing robust APIs for AI services.
- Proficient in software development best practices, including version control (Git), CI/CD pipelines, comprehensive testing, and code reviews.
- Strong understanding of agile methodologies, application resiliency, and security principles applied to complex AI projects.
- Proven expertise in system design, application development, and ensuring operational stability for AI initiatives.
- Deep experience with application and data architecture patterns and designs.
- Experience leveraging managed services and existing platforms, with a strong emphasis on API-First Design, microservices, and event-driven architectures.
- Hands-on experience with Docker and Kubernetes.
- Excellent analytical and innovative problem-solving skills, with a pragmatic and creative approach to overcoming complex technical challenges.
- Previous experience within the banking or financial services industry, understanding regulatory environments and specific challenges a plus.
- Proficiency in database technologies, such as Oracle, Postgres, or MongoDB.
- Nice to Have:
- Proficiency in UI (e.g., Angular, React, Next.js, Node.js, TypeScript) for full-stack development.
- Java (e.g., Spring Boot, Spring Cloud, Spring Security).
- Work Experience 10+ years of progressive software engineering experience with a strong emphasis on hands-on coding, demonstrating a proven track record of rapid delivery and successfully launching multiple AI features into production environments.
- Minimum 3+ years of dedicated professional experience in software development focused on AI, prompt engineering, machine learning, Generative and/or agentic AI systems.
- Strong hands-on experience with architecting and delivering enterprise scale AI projects.
- Motivated self-starter with the ability to quickly learn new skills and effectively navigate complex organizational structures.
- Bachelor’s degree in Computer Science, Information Technology, Artificial Intelligence, Robotics, or a related quantitative field; a Master's degree is preferred.

Qualifications

- Deep hands-on experience in engineering and executing scalable enterprise solutions.
- Expert-level proficiency in Python (e.g., FastAPI, Django, Flask, PySpark)
- Solid understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems.
- Hands-on experience with relevant frameworks (e.g., Google ADK, LanGraph, LangChain, AutoGen, CrewAI, N8N).
- Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and relevant libraries (e.g., Scikit-Learn, NumPy, Pandas).
- Proven experience in creating, deploying, and integrating
- MCPs (Model Context Protocol)
- into agentic AI systems.
- Deep familiarity with large language models (LLMs) such as ChatGPT, Claude, Gemini, and Llama, including their application within agentic systems.
- Demonstrated experience in designing and implementing robust APIs for AI services.
- Proficient in software development best practices, including version control (Git), CI/CD pipelines, comprehensive testing, and code reviews.
- Strong understanding of agile methodologies, application resiliency, and security principles applied to complex AI projects.
- Proven expertise in system design, application development, and ensuring operational stability for AI initiatives.
- Deep experience with application and data architecture patterns and designs.
- Experience leveraging managed services and existing platforms, with a strong emphasis on API-First Design, microservices, and event-driven architectures.
- Hands-on experience with Docker and Kubernetes.
- Excellent analytical and innovative problem-solving skills, with a pragmatic and creative approach to overcoming complex technical challenges.
- Previous experience within the banking or financial services industry, understanding regulatory environments and specific challenges a plus.
- Proficiency in database technologies, such as Oracle, Postgres, or MongoDB.
- Nice to Have:
- Proficiency in UI (e.g., Angular, React, Next.js, Node.js, TypeScript) for full-stack development.
- Java (e.g., Spring Boot, Spring Cloud, Spring Security).
- Work Experience 10+ years of progressive software engineering experience with a strong emphasis on hands-on coding, demonstrating a proven track record of rapid delivery and successfully launching multiple AI features into production environments.
- Minimum 3+ years of dedicated professional experience in software development focused on AI, prompt engineering, machine learning, Generative and/or agentic AI systems.
- Strong hands-on experience with architecting and delivering enterprise scale AI projects.
- Motivated self-starter with the ability to quickly learn new skills and effectively navigate complex organizational structures.
- Bachelor’s degree in Computer Science, Information Technology, Artificial Intelligence, Robotics, or a related quantitative field; a Master's degree is preferred.

Responsibilities

- Spearhead the end-to-end design, 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.
- Build full-stack applications that seamlessly integrate state-of-the-art ML/LLM tools and services into comprehensive AI solutions.
- Champion an MVP-first approach, focusing on rapid iterations, hypothesis testing, and A/B experiments to achieve continuous improvement and quick "time to value."
- Design and implement rigorous metrics and evaluation strategies for AI system and agent performance
- driving continuous optimization and behavioral improvement.
- Proactively explore, prototype (POC), and integrate the latest advancements in AI, particularly in agent-based systems, autonomous AI, and generative AI technologies.
- Provide hands-on technical leadership, guiding architectural decisions, and 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.
- Exhibit excellent communication and collaboration skills, effectively engaging with diverse stakeholders.

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