NEWPosted 3 hours ago

Job ID: JOB_ID_5296

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. If you are passionate about innovation, technical leadership, and influencing strategic direction, we encourage you to apply.

Key Responsibilities:

  • 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: Be part of 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 (e.g., databases, APIs) and unstructured data (e.g., documents, emails, free text), 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 (e.g., AWS SageMaker, Azure ML, Google AI Platform) 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.
  • 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: 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.

Required Skills & Technical Expertise:

  • Experience: 10-15 years of relevant experience in an 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.
  • Programming Fluency: Proficiency in at least two programming languages. Strong preference for Python with significant experience in JavaScript, TypeScript, and Golang being highly valued.
  • Scalable Solutions: Demonstrated deep hands-on experience in engineering and deploying enterprise-grade solutions that are highly scalable, resilient, and performant.
  • Generative AI Expertise: 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 critical for business process automation, vector stores (e.g., Pinecone, FAISS, Chroma DB), 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.
  • Data & Database Proficiency: Extensive experience with data analysis and manipulation using tools like SQL and Pandas. Proficiency in database technologies including Oracle, Postgres, or MongoDB.
  • API Integration: Proven experience in designing and implementing robust REST and WebSocket APIs. Experience with messaging and integration platforms like Kafka or JMS/MQ.
  • Production AI/ML/GenAI: Demonstrated ability to design, develop, and deploy GenAI and Agentic AI solutions into production environments. MLOps experience with MLOps principles and tools is a significant advantage.
  • Technical Proficiency: Extensive experience in system analysis and in programming of software applications with deep expertise in Python for AI/ML development.
  • Communication: Consistently demonstrates clear and concise written and verbal communication, capable of articulating complex technical concepts to both technical and non-technical audiences.

Compensation & Location

Salary: $130,000 – $170,000 per year (Estimated)

Location: Tampa, FL

Recruiter / Company – Contact Information

Recruiter / Employer: GAC Solutions

Email: veena@gacsol.com

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