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Production AI Engineer - Vice President

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Citigroup Inc.
Full Time position
Listed on 2026-07-24
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 70000 - 110000 GBP Yearly GBP 70000.00 110000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

The 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 agentsa, generative AI, and self-ahealing 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.
Qualifications
  • 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 expertise in prompt engineering
    : designing, iterating, and evaluating prompts for production use cases including classification, summarisation, code generation, and autonomous decision‑making.
  • Experience designing and deploying agentic systems using frameworks such as Lang Chain, Lang Graph, Auto Gen, CrewAI, or equivalent — including multi‑agent orchestration and tool‑use patterns.
  • Excellent engineering skills and…
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