Senior Lead - Java Full Stack - Senior Vice Presient
Listed on 2026-06-17
-
IT/Tech
AI Engineer (Applied/Software)
Senior Lead
- Java Full Stack
- Senior Vice Presient Job Req :
Pune, Maharashtra, India
Job Type:Hybrid
Posted:May. 18, 2026
Discover your future at CitiWorking at Citi is far more than just a job. A career with us means joining a team of more than 230,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.
Job OverviewThe Production Engineer is a pivotal role within Citi's Technology organisation, responsible for designing, building, and operating the intelligent systems that underpin our global production environment. This is an engineering-first position at the intersection of software craftsmanship, AI-native development, and large-scale distributed systems.
As part of a multi-year transformation journey, the successful candidate will help define what production engineering looks like in an era of autonomous agents, generative AI, and self-healing infrastructure. You will be expected to write production-grade code daily, design agentic workflows, and contribute meaningfully to the evolution of our AI engineering practices across Citi's India technology hub.
The role requires a comprehensive understanding of multiple areas within a function and how they interact to achieve the objectives of the function. Applies in-depth understanding of the business impact of technical contributions. Accountable for delivery of a full range of end-to-end projects.
Excellent communication skills required to negotiate internally. Involved in short- to medium-term planning of actions and resources for own area.
Responsibilities- Designs, develops, and maintains production-grade software systems with a strong emphasis on reliability, scalability, and operational excellence across Citi's global technology estate.
- Architects and implements agentic AI workflows — building autonomous systems that can reason, plan, and act across production environments with minimal human intervention.
- Applies advanced prompt engineering techniques to integrate large language models (LLMs) into operational tooling, incident response pipelines, and developer productivity platforms.
- Leads the development of AI-native observability solutions — leveraging intelligent agents to detect anomalies, predict failures, and automate remediation before issues impact end users.
- Writes clean, well-tested, and well-documented code across the full stack; champions engineering best practices including code review, pair programming, and test-driven development.
- Drives Continuous Delivery and Automation efforts across supported applications by means of Root Cause Analysis reviews, knowledge management, performance tuning, and user training.
- Operates and evolves CI/CD pipelines, Infrastructure-as-Code tooling, and Git Ops workflows to support rapid, safe delivery of software at scale.
- Collaborates with platform, data, and product engineering teams to embed AI capabilities into the production lifecycle — from deployment to decommission.
- Implements the Agile Framework through one of its implementations (SCRUM or Kanban) and ensures it integrates with overall organisation processes.
- Operates within a highly regulated financial environment, maintaining in-depth understanding of compliance requirements and their implications for system design and data handling.
- Coaches and mentors team members on AI engineering practices, prompt design patterns, and agentic system architecture — fostering a culture of continuous learning and technical excellence.
- Avidly communicates progress and project status across the organisation and ensures that stakeholders are managed appropriately throughout the execution period.
- Fosters a culture that promotes transparency and innovation for increased team productivity.
- Demonstrable experience in a critical software engineering or production engineering role with high business impact and a strong programming foundation (Java, Python, Go, or equivalent).
- Hands‑on experience with AI/ML engineering — including working with LLM APIs (OpenAI, Anthropic, Gemini, or open-source equivalents), embedding models, and vector databases.
- Proven…
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