GenAI Engineering Lead Job at Citi (Pune)

Job Description

We are seeking an exceptional and highly motivated GenAI Tech Lead to join our dynamic team and drive the design, prototyping, and implementation of advanced Generative AI solutions within Finance Technology. This pivotal role requires a seasoned professional with a deep understanding of Generative AI technologies, a strong hands-on approach, and a proven ability to translate complex business challenges into robust, scalable, and impactful digital solutions, particularly focusing on GenAI adoption and Agentic AI for automating business processes within the financial sector.

Job Responsibility

Strategic Leadership & GenAI Adoption: Drive the identification, evaluation, and adoption of emerging Generative AI technologies and tools to develop innovative solutions and enhance existing platforms. Actively design, develop, and implement AI/ML solutions within financial applications, with a strong emphasis on practical GenAI adoption. This includes hands-on coding, prototyping, and deploying GenAI solutions
Agentic AI for Business Process Automation: Lead the end-to-end design, prototyping, and implementation of Agentic AI solutions focused on automating critical business processes, ensuring they address business needs and scale effectively across the enterprise. This includes designing and implementing Retrieval Augmented Generation (RAG) systems to enhance accuracy and contextuality, especially for financial data
Chatbot Development: Design, develop, and deploy intelligent chatbot solutions capable of interacting with users across both structured data sources and unstructured data, leveraging GenAI for natural language understanding and generation in complex conversational flows
Document Processing & OCR Integration: Implement solutions for processing and extracting information from documents, including integrating Optical Character Recognition (OCR) technologies to handle scanned documents and images, making their content available for GenAI models
Text-to-SQL Implementation: Develop and deploy solutions leveraging Large Language Models to facilitate Text-to-SQL capabilities, enabling users to generate SQL queries from natural language requests, thus simplifying data access and analysis from structured databases
Data Analysis & Feature Engineering: Analyze large, complex datasets, identify intricate patterns, and extract actionable insights, leveraging GenAI capabilities for data augmentation or synthetic data generation, particularly relevant for Agentic AI applications
Data Pipeline Development: Build and maintain robust, scalable data pipelines for data ingestion, processing, and transformation, specifically optimizing for the unique requirements of GenAI model training and inference
Cross-Functional Collaboration: Partner with multiple management teams and business stakeholders to deeply understand requirements and translate them into precise technical specifications and actionable roadmaps, incorporating GenAI and Agentic AI possibilities into discussions
System Enhancements & Architecture: Identify and define necessary system enhancements to deploy new GenAI products and process improvements. Ensure application design adheres to the overall architecture blueprint, integrating GenAI and Agentic AI components seamlessly
Problem Resolution: Resolve a variety of high-impact problems/projects through in-depth evaluation of complex business processes, system processes, and industry standards, applying GenAI and Agentic AI where they can offer innovative solutions
Tool & Technology Evaluation: Evaluate and select appropriate Generative AI tools and technologies, including specialized frameworks, libraries, and cloud AI services with a focus on GenAI adoption and Agentic AI capabilities
Documentation & Monitoring: Develop and maintain comprehensive documentation for AI/ML models and systems, specifically addressing GenAI and Agentic AI implementations. Manage and monitor the performance, efficiency, and reliability of deployed AI/ML models, including evaluating the effectiveness of GenAI components in production
Technical Mentorship & Leadership: Provide guidance and mentorship to junior engineers and analysts, fostering best practices in GenAI and Agentic AI development, deployment, and operational excellence, and allocating work as necessary
Risk Assessment: Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency, especially concerning responsible AI and GenAI ethics in the context of GenAI adoption and Agentic AI
Agile Development & Proof-of-Concept: Champion rapid delivery and iterative development, prioritizing value delivery over upfront perfection. Lead the development of compelling proof-of-concept projects to validate the feasibility and potential of novel GenAI and Agentic AI solutions
Platform Contribution: Actively contribute to the design and development of internal GenAI and Agentic AI platforms, frameworks, and shared services
Troubleshooting Support: Provide expert technical support, troubleshooting, and resolution for GenAI and Agentic AI solutions in production environments

Requirements

10-15 years of relevant experience in Apps Development or systems analysis role, with a significant portion dedicated to AI/ML and demonstrable hands-on experience in designing, building, and deploying real-world Generative AI solutions, with a specific focus on GenAI adoption and Agentic AI for business process automation
Proficiency in at least two programming languages. Strong preference for Python, with significant experience in Javascript/Typescript and Golang being highly valued
Demonstrated deep hands-on experience in engineering and deploying enterprise-grade solutions that are highly scalable, resilient, and performant
Strong theoretical and practical understanding of Large Language Models (LLMs), including experience with various open-source and proprietary models, fine-tuning techniques, and deployment strategies
Proficiency with transformers, agentic frameworks, vector stores, and advanced search algorithms
Hands-on experience with Retrieval Augmented Generation (RAG) implementations
Experience with relevant GenAI/ML frameworks such as LangChain, LangGraph, MLFlow, Spring AI, Spring Boot, and Flask
Extensive experience with data analysis and manipulation using tools like SQL and Pandas
Proficiency in database technologies including Oracle, Postgres, or MongoDB
Proven experience in designing and implementing robust REST and WebSocket APIs
Experience with messaging and integration platforms like Kafka or JMS/MQ
UI development skills with technologies such as React JS or Streamlit
Demonstrated ability to design, develop, and deploy GenAI and Agentic AI solutions into production environments
Experience with MLOps principles and tools is a significant advantage
Extensive experience in system analysis and in programming of software applications, with deep expertise in Python for AI/ML development
Consistently demonstrates clear and concise written and verbal communication, capable of articulating complex technical concepts to both technical and non-technical stakeholders
Experience in managing and implementing successful projects
demonstrated leadership and project management skills within an agile development framework
Subject Matter Expert (SME) in at least one area of Applications Development or AI/ML domain, with a strong understanding of financial services concepts preferred
Ability to adjust priorities quickly as circumstances dictate in a fast-paced environment
Bachelor’s degree/University degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent experience. Master’s degree or Ph.D. preferred, especially with a focus on Artificial Intelligence, Machine Learning, or Natural Language Processing
10+ years of professional experience, preferably within financial services or leading technology firms
A self-starter with a strong drive for innovation, exhibiting exceptional problem-solving skills, and a knack for leveraging "out-of-the-box" tooling and automation

Citi - All Job Offers

Select Country

GenAI Engineering Lead

Job Description

Job Responsibility

Requirements

Looking for more opportunities?

GenAI Engineering Lead

GenAI Engineering Development Lead VP

Lead GenAI Lead Engineer, Innovation Labs – SVP

Lead GenAI Lead Engineer/Architect, Innovation Labs - SVP

Program Lead - GenAI Product Planning and Operations

Gen AI Adoption Lead (Engineering Productivity)

Senior Test Automation & AI Quality Engineering Lead - VOIS

Python Genai Lead Engineer - Assistant Vice President

Ml Tech Lead (genai, Aws)

Our AI answers in your language