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*Job Overview**
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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 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**
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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 GitOps 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.
*Qualifications**
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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 LangChain, LangGraph, AutoGen, CrewAI, or equivalent — including multi\-agent orchestration and tool\-use patterns.
Excellent engineering skills and strong understanding of **Software Development Lifecycle**, GitOps, and modern DevSecOps 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 of deploying and running services at scale on top of **Docker/Kubernetes** stack and a service mesh (Istio or equivalent) is highly desirable.
*Human Qualities \& Soft Skills**
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Beyond technical capability, the Production Engineer who will thrive in this role brings a distinct set of human qualities that amplify their engineering impact and elevate those around them.
**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.
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*Job Family Group:**
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Technology
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*Job Family:**
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Applications Development
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*Time Type:**
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Full time
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*Most Relevant Skills**
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Please see the requirements listed above.
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*Other Relevant Skills**
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For complementary skills, please see above and/or contact the recruiter.
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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.*
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.
Operational experience with orchestration tools for **CI/CD and Infrastructure\-as\-Code** tooling (Terraform, CloudFormation, 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, AppDynamics, 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.