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Production AI Engineer - Vice President
LondonSource: WhatJobs
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Overview
In this Production Engineer role, you’ll design, build, and run AI-enabled, production-grade software at scale within Citi’s technology estate. You’ll define agentic workflows and contribute to AI engineering practices across Citi’s India hub during a multi-year transformation. You write reliable code daily, implement observability and automation, and collaborate with cross-functional teams to embed AI into the production lifecycle. This is a hands-on, engineering-led opportunity to shape autonomous systems in a regulated financial environment.
Pay / Benefits
27 days annual leave (plus bank holidays)
Discretionary annual bonus
Private Medical Care & Life Insurance
Employee Assistance Program
Pension Plan
Paid Parental Leave
Responsibilities
Design, develop, and maintain production-grade software with reliability and operational excellence
Architect and implement agentic AI workflows for autonomous production environments
Integrate LLMs into tooling and incident response via advanced prompt engineering
Develop AI-native observability for anomaly detection and automated remediation
Write clean, tested code and promote best practices (code review, pair programming, TDD)
Drive Continuous Delivery, automation, RCAs, and knowledge sharing
Manage CI/CD pipelines, IaC tooling, and GitOps for scalable delivery
Collaborate with platform, data, and product teams to embed AI across deployment lifecycle
Implement Agile (SCRUM or Kanban) and align with organizational processes
Operate in a regulated environment with strong compliance awareness
Coach peers on AI engineering practices and agentic system design
Communicate progress to stakeholders and foster transparent, innovative culture
Key requirements
Proven experience in a critical software or production engineering role with high business impact
Strong programming foundation (Java, Python, Go, or equivalent)
Hands-on AI/ML engineering with LLM APIs and embeddings
Expertise in prompt engineering for production use cases
Experience designing/ deploying agentic systems using LangChain, LangGraph, AutoGen, CrewAI, or equivalents
Solid understanding of SDLC, GitOps, and modern DevSecOps
Knowledge of computer science concepts (networks, OS, virtualization, containers)
Polyglot full-stack mindset and ability to learn new languages
Experience deploying services at scale on Docker/Kubernetes and service mesh (Istio)
Experience with CI/CD and IaC tools (Terraform, CloudFormation, Pulumi)
Experience delivering software with Agile (SCRUM/Kanban)
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