Production AI Engineer - Vice President

Production AI Engineer - Vice President

Full-Time 70000 - 90000 £ / year (est.) No working from home possible
Citigroup, Inc.

At a Glance

  • Tasks: Design and build intelligent systems for a global production environment using cutting-edge AI technologies.
  • Company: Join Citi, a leading financial services company with a focus on innovation.
  • Benefits: Enjoy 27 days annual leave, private medical care, and a competitive salary.
  • Other info: Be part of a culture that promotes transparency, innovation, and continuous learning.
  • Why this job: Make a real impact in AI engineering while working in a dynamic, hybrid environment.
  • Qualifications: Strong programming skills and experience in AI/ML engineering are essential.

The predicted salary is between 70000 - 90000 £ per year.

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 (Open AI, 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, Crew AI, or equivalent — including multi‑agent orchestration and tool‑use patterns.
  • Excellent engineering skills and strong understanding of

Software Development Lifecycle , Git Ops, and modern Dev Sec Ops practices.

  • Excellent working knowledge of key computer science concepts (networking, operating systems, virtualisation, containerisation, etc.).
  • Polyglot full‑stack developer mentality and ability to pick up new languages and skills.
  • Excellent debugging and analytical skills: ability to isolate root cause across networking/infrastructure, application, and database stacks.
  • Operational experience deploying and running services at scale on top of Docker/Kubernetes stack and a service mesh (Istio or equivalent) is highly desirable.
  • Operational experience with orchestration tools for CI/CD and Infrastructure-as-Code tooling (Terraform, Cloud Formation, Pulumi, etc.) is highly desirable.
  • Experience of delivering software using

Agile delivery methodologies is a must (SCRUM/Kanban).

  • Operational experience of using middleware technologies (MQ, Apache Kafka, etc.) to run services at scale is desirable.
  • Strong experience with end-to-end observability stacks

(Datadog, App Dynamics, Dynatrace, etc.) is desirable.

  • Degree in Computer Science, Mathematics, Physics, or a related technical subject is desirable.
  • Experience of senior stakeholder management.
  • Consistently demonstrates clear and concise written and verbal communication skills.
  • Ability to operate in a global environment with on‑/near‑/off‑shore matrix reporting structures.
  • Qualities that Matter
  • Learnability

— Rapidly acquires new skills, frameworks, and paradigms. In a field evolving as fast as AI engineering, the ability to learn is the most durable skill of all.

Teachability

— Receives feedback with openness and intellectual humility. Actively seeks mentorship and applies guidance to accelerate growth.

Flexibility & Adaptability

— Thrives in ambiguity. Pivots gracefully when requirements shift, technology evolves, or priorities change — without losing momentum or quality.

Engineering Mindset

— Approaches every problem systematically: decomposing complexity, forming hypotheses, and validating solutions with rigour and precision.

Product‑Minded Thinking

— Understands that code serves users and business outcomes. Balances technical elegance with pragmatic delivery and user impact.

Collaborative Spirit

— Builds trust across disciplines — engineering, product, operations, and leadership. Elevates the team’s collective output through generosity and clear communication.

Intellectual Curiosity

— Asks “why” before “how”. Explores the edges of what’s possible with AI and production systems, driven by genuine fascination rather than obligation.

Ownership & Accountability

— Takes end‑to‑end responsibility for what they build. Does not hand off problems — follows through from design to deployment to post‑incident review.

What we’ll provide you

By joining Citi, you will not only be part of a business casual workplace with a hybrid working model (up to 2 days working at home per week), but also receive a competitive base salary (which is annually reviewed), and enjoy a whole host of additional benefits such as:

  • 27 days annual leave (plus bank holidays)
  • A discretional annual performance related bonus
  • Private Medical Care & Life Insurance
  • Employee Assistance Program
  • Pension Plan
  • Paid Parental Leave Special discounts for employees, family, and friends
  • Access to an array of learning and development resources

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.

View Citi’s EEO Policy Statement and the Know Your Rights poster.

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Production AI Engineer - Vice President employer: Citigroup, Inc.

Citi London is an exceptional employer, offering a dynamic and inclusive work environment that fosters innovation and collaboration. With a competitive salary, generous annual leave, and a hybrid working model, employees enjoy a healthy work-life balance while having access to extensive learning and development resources. As a key player in the Equity Derivatives Technology team, you will have the opportunity to lead impactful projects and grow your career within a globally recognised financial institution.

Citigroup, Inc.

Contact Details:

Citigroup, Inc. Recruitment Team

We think you need these skills to ace Production AI Engineer - Vice President

Production Engineering
Software Development Lifecycle
AI/ML Engineering
Prompt Engineering
Agentic Systems Design
Full-Stack Development
DevSecOps Practices