Discover Your Future in Credit Risk Technology
Build systems that shape credit decisions—at scale.
Join a fast-moving Credit Risk Technology team where modern engineering, data, and AI come together to drive real-world financial impact. We operate with a startup mindset—ownership, speed, and experimentation—within the rigor and responsibility of a global financial institution. You’ll help design and deliver mission-critical platforms that support credit risk assessment, analytics, and decisioning across the firm.
Job Overview
The Credit Risk Applications Technology Lead Analyst is a senior engineering leadership role focused on building and evolving modern, scalable platforms for credit risk management. You will lead application design and development while partnering closely with risk, data, and platform teams to deliver systems that are performant, resilient, and compliant.
This role blends hands-on development, system architecture, technical leadership, and AI-enabled innovation, with a strong emphasis on microservices, cloud-native design, and enterprise-grade governance.
Key Responsibilities
- Architect, design, and deliver scalable, Python-based applications supporting credit risk analytics, workflows, and reporting.
- Partner with risk, product, and technology leadership to integrate platforms, identify enhancements, and enable new products and process improvements.
- Resolve high-impact, complex initiatives through deep analysis of business processes, system flows, and industry standards.
- Ensure solutions adhere to enterprise architecture, data, security, and infrastructure blueprints.
- Establish and enforce engineering standards for coding, testing, CI/CD, debugging, and production readiness.
- Design and evolve microservices-based architectures, ensuring scalability, resiliency, observability, and maintainability.
- Apply AI and GenAI capabilities to modernize workflows, automate analysis, and unlock new insights in credit risk.
- Serve as technical leader and mentor, coaching mid-level engineers and analysts and allocating work as needed.
- Apply sound risk and control judgment, ensuring compliance with laws, regulations, and policies while safeguarding clients, data, and the firm.
How You’ll Work
- Operate with a startup mindset: ownership, bias for action, and pragmatic innovation.
- Deliver with enterprise discipline: stability, controls, transparency, and audit readiness.
- Balance experimentation with responsibility in a high-trust, high-impact environment.
- Adapt quickly as priorities change while maintaining long-term system integrity.
Core Technical Skills
- 10–15 years of experience in application development or systems engineering within complex environments.
- Advanced proficiency in Python and SQL, with strong software engineering fundamentals.
- Hands-on experience building API-driven services using FastAPI, Pydantic, and/or Django.
- Proven expertise designing and implementing microservices architectures, including service decomposition, inter-service communication, resiliency patterns, and observability.
- Strong experience with Docker and Kubernetes, deploying and operating containerized services in production.
- Deep understanding of system architecture, data flows, and distributed systems.
- Experience working in Linux environments, including shell scripting and operational troubleshooting.
- Strong track record implementing unit testing, TDD, and automated quality controls.
- Subject Matter Expert (SME) in at least one application, platform, or service domain.
AI & Modern Engineering Tools
- Working knowledge of large language models (LLMs) and modern AI platforms from leading providers such as OpenAI, Anthropic, Google, and Meta.
- Experience designing or contributing to LLM-enabled solutions (e.g., copilots, workflow automation, analytics augmentation).
- Familiarity with prompt engineering, model integration patterns, and AI governance considerations in enterprise environments.
- Exposure to modern “vibe coding” practices—leveraging AI-assisted tooling to accelerate development, experimentation, and problem solving while maintaining engineering rigor.
Bonus / Differentiating Skills
- Experience with distributed data and compute platforms (e.g., Spark, PySpark, Hadoop, Hive).
- Hands-on experience with graph databases, particularly Neo4j, for network, relationship, or dependency-driven use cases.
- Background in credit risk, financial risk management, or banking platforms.
- Experience modernizing or decomposing legacy monolithic systems in large enterprises.
- Proven delivery of GenAI / AI-driven solutions in regulated or large-scale environments.
Education
Bachelor’s degree (or equivalent experience) in Computer Science, Engineering, Mathematics, or a related STEM field.
Master’s degree preferred.
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Job Family Group: Technology------------------------------------------------------
Job Family:Applications Development------------------------------------------------------
Time Type:Full time------------------------------------------------------
Most Relevant Skills Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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.
Skills Required
- 10–15 years of experience in application development or systems engineering within complex environments
- Advanced proficiency in Python and SQL
- Experience building API-driven services using FastAPI, Pydantic, and/or Django
- Expertise designing and implementing microservices architectures
- Strong experience with Docker and Kubernetes in production
- Deep understanding of system architecture, data flows, and distributed systems
- Experience working in Linux environments, including shell scripting and operational troubleshooting
- Experience implementing unit testing, TDD, and automated quality controls
- Subject matter expertise in at least one application, platform, or service domain
- Working knowledge of large language models and modern AI platforms
- Experience designing or contributing to LLM-enabled solutions
- Familiarity with prompt engineering, model integration patterns, and enterprise AI governance
- Bachelor’s degree or equivalent experience in Computer Science, Engineering, Mathematics, or a related STEM field
- Master’s degree
- Experience with Spark, PySpark, Hadoop, or Hive
- Hands-on experience with Neo4j or other graph databases
- Background in credit risk, financial risk management, or banking platforms
- Experience modernizing or decomposing legacy monolithic systems
- Proven delivery of GenAI or AI-driven solutions in regulated or large-scale environments
Citi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.
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Healthcare Strength — Benefits coverage is positioned as comprehensive, including health, dental, and vision insurance plus on-site clinics, prescription drug support, and disability coverage. Family-building support such as fertility assistance is described as a notable differentiator within the overall package.
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Retirement Support — Retirement benefits are framed as strong, highlighted by a 401(k) with matching and additional plan options like a Roth 401(k). Financial support is reinforced through discounts and broader financial guidance resources tied to the benefits ecosystem.
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Wellbeing & Lifestyle Benefits — Wellbeing support extends beyond insurance through programs like an Employee Assistance Program, counseling/legal resources, and gym or wellness reimbursement. These offerings increase the perceived total rewards value even when cash compensation sentiment varies by role.
Citi Insights
What We Do
Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients. We have 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. We are Citi, the global bank – an institution connecting millions of people across hundreds of countries and cities.
