Описание
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.
Задачи
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. 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.
Требования
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. Experience of delivering software using Agile delivery methodologies is a must (SCRUM/Kanban). 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. 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.
Будет плюсом
- 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
- Operational experience with orchestration tools for CI/CD and Infrastructure-as-Code tooling (Terraform, CloudFormation, Pulumi, etc.) is highly desirable
- 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
Условия
- business casual workplace with a hybrid working model (up to 2 days working at home per week)
- competitive base salary (which is annually reviewed)
- 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
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Production AI engineer employer: Citi
Citi is an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration within the Equities Technology team. Employees benefit from cutting-edge technology, opportunities for professional growth, and a culture that values diversity and inclusion. With a focus on high-performance analytics and real-time data solutions, Citi empowers its engineers to make impactful contributions while enjoying a supportive atmosphere in a globally recognized financial institution.
StudySmarter Expert Advice🤫
We think this is how you could land Production AI engineer
✨Join Local Manufacturing Groups
Getting involved in local manufacturing groups or associations can seriously boost your visibility. These groups often have insider info on job openings and networking events, plus they help you connect with like-minded folks in the industry. Check out what's happening in your area!
✨Show Off Your Skills in Practical Spaces
Consider participating in workshops or open days at manufacturing companies. It's a great way to show off your hands-on skills in a real-world environment and can sometimes lead to job offers right on the spot. Keep an eye on announcements from local manufacturers for these opportunities!
✨Leverage the Power of Internships
While you're looking for full-time positions, don't underestimate the power of internships! Even if you don't see a direct role, securing an internship at a company can open doors to future jobs. Many manufacturing firms prefer to hire from their intern pool, so it's definitely worth considering.
✨Apply Directly Through Company Websites
When you find a role at a company you love, like Citi, apply directly on their website. This way, you’re more likely to be noticed by the hiring team. Plus, showing that you took the time to seek out their application process highlights your genuine interest in the firm!
Some tips for your application 🫡
Showcase Your Technical Skills:In the manufacturing-production sector, it's crucial to highlight your technical skills and experience. Make sure your CV features any relevant qualifications, such as certifications in machinery operation or production management, and don’t forget about any specific systems or software you’re familiar with. This can really set you apart!
Emphasise Teamwork and Communication:Working in manufacturing often means being part of a larger team. Highlight your experience in collaborative projects or environments where communication was key. Maybe you have experience with lean manufacturing principles? Talk about how you worked with your team to improve productivity and maintain quality.
Tailor Your Cover Letter to the Company:Don’t just recycle an old cover letter! Take the time to tailor your cover letter to Citi specifically. Mention what excites you about their production processes or products, and how your previous experiences can contribute to their goals. We want to see your enthusiasm for the role!
Use Concrete Examples of Your Achievements:When detailing your work experience, include measurable achievements that can demonstrate your impact. Whether it’s improving efficiency by a certain percentage or successfully leading a project, these specifics can make a huge difference. Numbers speak volumes in the manufacturing world!
How to prepare for a job interview at Citi
✨Know Your Manufacturing Processes
Before you walk into the interview with Citi, brush up on the specific manufacturing processes relevant to the role. Understanding lean manufacturing principles or quality control techniques could give you a solid edge to discuss how you’d fit into their operations.
✨Technical Questions Are Key
Be prepared for technical questions around machinery, production scheduling, or materials handling. Make sure you can confidently explain how you've dealt with these in past experiences or internships. Knowing industry-specific software could also be a big plus!
✨Showcase Your Problem-Solving Skills
Manufacturing environments often focus on continuous improvement. Be ready to discuss specific instances where you’ve solved a production issue or implemented a process improvement. It’s all about demonstrating your analytical thinking and hands-on approach.
✨Align Your Values with Quality and Safety
In a full-time role, companies like Citi value commitment to quality and safety. Be prepared to discuss how you prioritise these factors in your work. It’s about showing that you’re not just looking for a job, but that you genuinely care about contributing positively to their production environment.
