The Applications Development Technology Lead Analyst is a senior level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to lead applications systems analysis and programming activities.
Responsibilities:
- Lead AI agent development, architecture, and deployment using GenAI platforms, microservices, advanced NLP/NLU, and intelligent bot interactions, leveraging script tools for system enhancements.
- Architect and build autonomous AI systems for problem-solving and decision-making, ensuring seamless and secure integration with enterprise systems via robust APIs.
- Implement secure, scalable data storage for conversational AI using diverse databases (MongoDB, SQL, NoSQL), adhering to data governance policies.
- Develop highly resilient systems with advanced error handling, fault tolerance, and intelligent routing for optimal user experience.
- Drive GenAI thought leadership, integrating emerging platforms (Gemini, Claude, GPT) and research, while staying current with the latest technologies and trends.
- Deliver end-to-end Agentic AI solutions, focusing on Python backend services (FastAPI, asyncio), secure REST APIs, and robust data pipelines, applying fundamental programming principles.
- Optimize AI agent performance, latency, and cost through profiling, caching strategies, and distributed system optimization.
- Establish CI/CD practices for automated testing, agent evaluation, cloud-native deployment, and ensure code quality through reviews and peer programming.
- Collaborate extensively with cross-functional teams and stakeholders to gather requirements, brainstorm solutions, deliver high-quality software, and consult on technical issues.
- Analyze applications for vulnerabilities, conduct thorough testing, debugging, and effectively troubleshoot software issues.
- Mentor and coach engineering teams, act as a Subject Matter Expert (SME), and contribute to continuous learning initiatives.
- Assess and manage risks in business decisions, safeguarding the firm's reputation, ensuring compliance with regulations, and transparently escalating control issues.
Recommended Qualifications:
- Extensive hands-on experience with GenAI concepts, Large Language Models (LLMs), transformer architectures, RAG, and agentic frameworks (e.g., LangChain, LangGraph, Google ADK).
- Expert Python proficiency for AI/ML development, data engineering, and backend services; deep understanding of software design patterns, data structures, and algorithms.
- Hands-on experience with AI Development Tools such as Google's AI Development Kit (ADK), Claude Code for AI-driven coding, and agent.MD or similar frameworks for autonomous agents.
- Proficient with containers and orchestration technologies, specifically OpenShift, and proven ability to architect and deploy high-performance, large-scale AI/ML systems to production.
- Strong grasp of modern software development principles, clean code practices, distributed systems, and expertise in database management (Relational, Vector, SQL, NoSQL, optimization).
- Extensive experience architecting and developing virtual assistants, chatbots, and conversational AI platforms.
- Expertise in front-end development with React/AngularJS and experience with technologies like Java, Spring Boot, SQL Queries is a plus.
Experience:
- 10+ years of software development experience, including Full Stack roles, with strong experience delivering Python and GenAI products into production.
- Proven expertise in LLMs, fine-tuning methods, building RAG systems (hybrid search, multi-vector retrieval), and practical knowledge of model optimization (compression, quantization) with tools like DeepSpeed, vLLM, GPTQ.
- Extensive experience with containerization (Docker), orchestration (Kubernetes), CI/CD pipelines for APIs and ML models, and MLOps practices in agile development environments.
- Experience with distributed systems, event-driven architectures, container-based microservices, distributed logs, and NoSQL databases.
- Competence with NodeJs, React, testing frameworks (PyTest, Playwright), and familiarity with Java/Spring Boot.
- Expert understanding of advanced NLP/NLU, Machine Learning, and Generative AI techniques, coupled with demonstrated experience in complex API integrations and enterprise system connectivity.
- Strong expertise in database management, data modeling, data security best practices, and proficiency with cloud platforms (AWS, Azure, GCP) including serverless and managed AI/ML services.
- Exceptional problem-solving, analytical, and communication skills, with the ability to lead, mentor cross-functional teams, and contribute to open-source GenAI/NLP projects.
Education:
- Bachelor’s degree/University degree or equivalent experience
- Master’s degree preferred
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
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Job Family Group: Technology------------------------------------------------------
Job Family:Applications Development------------------------------------------------------
Time Type:Full time------------------------------------------------------
Most Relevant Skills Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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Skills Required
- 10+ years software development experience including Full Stack roles
- Bachelor's degree or equivalent experience
- Extensive hands-on experience with GenAI, LLMs, transformer architectures, RAG, and agentic frameworks
- Expert-level Python proficiency for AI/ML development, data engineering, and backend services
- Experience with FastAPI, asyncio, and building secure REST APIs
- Experience with databases and data storage for conversational AI (MongoDB, SQL, NoSQL, vector DBs), data modeling and security
- Experience with containers and orchestration (Docker, Kubernetes) and specifically OpenShift
- Experience establishing CI/CD pipelines and MLOps practices for APIs and ML models
- Practical experience with model optimization and serving tools (DeepSpeed, vLLM, GPTQ)
- Proven experience architecting and developing virtual assistants, chatbots, and conversational AI platforms
- Proficiency with cloud platforms and managed AI/ML services (AWS, Azure, GCP)
- Competence with Node.js, React, and testing frameworks (PyTest, Playwright)
- Front-end development with React/AngularJS and experience with Java, Spring Boot, SQL queries
- Master's degree
Citi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.
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Healthcare Strength — Benefits coverage is positioned as comprehensive, including health, dental, and vision insurance plus on-site clinics, prescription drug support, and disability coverage. Family-building support such as fertility assistance is described as a notable differentiator within the overall package.
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Retirement Support — Retirement benefits are framed as strong, highlighted by a 401(k) with matching and additional plan options like a Roth 401(k). Financial support is reinforced through discounts and broader financial guidance resources tied to the benefits ecosystem.
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Wellbeing & Lifestyle Benefits — Wellbeing support extends beyond insurance through programs like an Employee Assistance Program, counseling/legal resources, and gym or wellness reimbursement. These offerings increase the perceived total rewards value even when cash compensation sentiment varies by role.
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