Responsibilities:
1. Software Development & System Design
- Architect, design, develop, and maintain robust, scalable, and high-performance applications supporting MTF.
- Lead the design of distributed, fault-tolerant, real-time systems capable of handling high-volume, low-latency trade processing across global markets.
- Champion the use of AI-assisted coding tools (e.g., GitHub Copilot or equivalent GenAI tools) to accelerate developer productivity, reduce toil, and improve code quality.
- Ensure code is clean, maintainable, and testable by adhering to SOLID principles, design patterns, and platform engineering standards.
- Actively contribute to hands-on coding, code reviews, and refactoring to maintain high engineering standards across the team.
- Own the technical design of key platform components, producing clear architecture documentation and decision records.
2. Engineering Excellence & AI-Driven Quality
- Champion Test-Driven Development (TDD), and high unit test coverage as non-negotiable engineering standards.
- Introduce AI-powered code review tooling to complement human reviews and catching security vulnerabilities, anti-patterns, and performance issues at scale.
- Apply predictive quality analytics to identify high-risk code changes before they reach production.
- Drive the adoption of automated testing frameworks across unit, integration, regression, and end-to-end test layers, including AI-assisted test generation.
- Implement and enforce secure coding practices, augmented by AI-driven vulnerability scanning, performing assessments and ensuring compliance with financial industry security and regulatory standards.
- Embed CI/CD pipelines and DevOps practices deeply into the team's delivery workflow, aligned to Citi Engineering Excellence Standards.
- Drive a culture of zero-defect engineering with proactive quality ownership from design through to production.
3. Platform & Domain Expertise
- Develop deep understanding of trade lifecycle, risk calculation, pnl calculation and estimates to make informed technical decisions aligned with business needs.
- Partner with business analysts, product owners, and operations teams to translate complex business logic and regulatory requirements into robust technical solutions.
- Ensure platform components meet SLA targets for availability, throughput, and latency in a mission-critical environment.
- Collaborate with downstream and upstream system owners across the MTF to ensure seamless integration and data integrity.
- Drive continuous platform modernization by improving maintainability, scalability, and operational efficiency
4. Technical Leadership & People Management
- Mentor engineers on AI tool usage, prompt engineering, and responsible AI practices, building internal AI literacy across the team.
- Partner with architects, platform engineers, and cross-functional teams to design scalable, distributed, and AI-ready systems.
- Lead technical discussions, architecture reviews, and design sessions by providing clear guidance on engineering decisions, AI integration patterns, and trade-offs.
- Drive capacity planning, technical roadmap execution, and engineering delivery commitments
- Represent the engineering team in stakeholder forums, providing transparent updates on delivery progress, risks, and technical health.
Skills and Qualifications
Must-Have Skills
1. Programming Languages
- Java Core backend development; deep expertise in production-grade Java applications
- Python Used for data pipelines, AI/ML integration, scripting, and automation
2. System Architecture (Real-Time, High-Throughput & Performance Optimization)
- Microservices Architecture Design and delivery of loosely coupled, independently deployable services at scale
- Event-Driven & Messaging Systems Hands-on experience with Kafka for real-time, high-throughput event streaming and messaging
- High Availability & Fault Tolerance Design patterns for resilient systems including circuit breakers, bulkheads, failover, and graceful degradation
- Databases Strong proficiency in Oracle (SQL) for transactional data and MongoDB (NoSQL) for flexible, high-throughput data models
3. Advanced Data & AI Integration
- GenAI Tooling Hands-on experience with AI-assisted development tools (GitHub Copilot, or equivalent) and LLM API integration
- Data Engineering Strong understanding of data pipelines, streaming data processing, and data quality patterns in high-volume environments
4. Cloud & DevOps — Citi Engineering Excellence Standards
- Cloud-Native Engineering Hands-on experience with AWS, Kubernetes, and Docker for scalable, containerized deployments
- CI/CD Pipelines Strong proficiency in building and maintaining CI/CD pipelines aligned to Citi Engineering Excellence Standards
- Trunk-Based Development Feature flags, progressive delivery, and continuous integration as core delivery practices
- Observability & Monitoring Experience with production monitoring, distributed tracing, intelligent alerting, and SRE practices
- Secure Engineering AI-augmented vulnerability assessments, secure coding standards, and compliance in regulated financial environments
- Agile Delivery Strong experience in Agile/SAFe frameworks on backlog management, sprint delivery, and cross-team dependency management
5. Good-to-Have Skills
- Knowledge of trade lifecycle, money market, risk engine and risk calculations.
- Understanding of regulatory compliance frameworks
- Knowledge of risk management, reconciliation, and exception handling patterns in settlement workflows.
- Familiarity with prompt engineering and usage of AI in software development
What We Are Looking For
This role is for an engineer at heart who has grown into a leader:
- Stays close to the code and actively participates in design, review, and technical problem-solving alongside the team.
- Thinks AI-first by actively seeks opportunities to apply AI and GenAI to engineering and operational challenges, not just product features.
- Owns outcomes by taking full accountability for platform quality, reliability, and delivery commitments.
- Thrives in complexity: comfortable navigating the technical and operational complexity of mission-critical financial systems.
- Raises the bar by consistently pushing for higher engineering standards, better test coverage, cleaner architecture, and more resilient systems.
- Embraces AI pragmatically by identifying high-value opportunities to apply AI/ML to real platform problems, without losing sight of engineering fundamentals.
- Inspires curiosity: creates an environment where engineers are excited to learn, experiment, and grow with AI.
Education:
- Bachelor’s degree/University degree or equivalent experience
- Master’s degree preferred
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Job Family Group:
Technology
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Job Family:
Applications Development
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Time Type:
Full time
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Primary Location Full Time Salary Range:
$120,800.00 - $170,800.00
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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Automated Processing and AI
We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
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This job opening is for an existing job vacancy.
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