C

Citi

Runs banking and payments for global clients

Client Servicing Solutions Lead

AI Application Engineering +1Confirmed live in the last 24 hours
Full-time$176.7k - $265.1kHybrid

About the Job

Requirements

  • Advanced daily use of AI-assisted development tools, including the ability to describe tools used, prompting methods, validation of generated output, and measurable effects on development velocity.
  • Expert-level proficiency in Java and the Spring Boot ecosystem, including Spring Security, Spring Data, Spring WebFlux, and Spring Integration.
  • Strong frontend capability in React and TypeScript, including feature-complete UI components, state management patterns, and API integration layers.
  • Deep experience with event-driven architecture, including Apache Kafka, schema registries, Avro serialization, consumer group management, and exactly-once delivery patterns.
  • Hands-on experience with BPM and workflow engines, BPMN modeling, saga orchestration, and long-running process management.
  • Proficiency in GraphQL API design, including federation, schema stitching, resolver optimization, and data loader patterns for high-throughput institutional data APIs.
  • Strong command of cloud-native patterns, including Kubernetes, service mesh, circuit breakers, and distributed tracing.
  • Rigorous testing discipline across unit, integration, contract (Pact), and performance testing, with measurable coverage standards and automated quality gates.
  • Advanced daily use of AI pair-programming tools such as GitHub Copilot, Devin, and Cursor, or equivalent, to accelerate feature delivery without sacrificing code quality.
  • Proficiency in prompt engineering for software development, including prompts for code generation, refactoring, test synthesis, and technical documentation across complex enterprise codebases.
  • Experience validating and reviewing AI-generated code, including understanding failure modes, hallucination risks, security implications, and ways to tune output for production readiness.
  • Hands-on experience building LLM-powered product features such as RAG pipelines, conversational search, document Q&A, or AI-assisted workflow interfaces using LangChain, LlamaIndex, or equivalent.
  • Ability to integrate LLM APIs such as OpenAI, Anthropic Claude, and AWS Bedrock securely into production Java/Spring Boot services, including rate limiting, fallback handling, and cost controls.
  • Understanding of AI governance in regulated environments, including model risk, data privacy constraints, and responsible AI practices relevant to financial services.
  • Working understanding of custody operations, including settlement instruction processing, DVP/FOP flows, mandatory and voluntary corporate actions, income collection, asset servicing, and reconciliation, sufficient to design and review implementing software.
  • Familiarity with fund administration workflows, including NAV calculation inputs, fund accounting transaction types, investor register management, transfer agency operations, and fund reporting data structures.
  • Knowledge of SWIFT MT/MX messages and ISO 20022 pain/camt/sese formats, and their mapping to internal Investor Services data models.
  • Understanding of institutional asset-servicing client onboarding and lifecycle management, including account opening, KYC/AML data requirements, mandate capture, and ongoing client instruction management.
  • Awareness of the regulatory context for custody and fund-services technology, including AIFMD, UCITS, SFTR reporting obligations, and audit trail requirements.
  • Understanding of multi-currency, multi-jurisdiction, multi-asset-class institutional operations data and its implications for software design.
  • Bachelor's degree or equivalent experience.

Responsibilities

  • Design, develop, test, and ship production-quality features across the Investor Services Workbench backend using Java/Spring Boot and frontend using React/TypeScript, contributing meaningful reviewed and merged code each sprint.
  • Use AI pair-programming tools for code generation, test synthesis, refactoring, documentation, and API design acceleration, and champion their adoption across delivery squads.
  • Apply custody and fund-services domain knowledge to translate business requirements into technically precise, implementation-ready specifications between operations subject-matter experts and engineering squads.
  • Design and build complex, multi-step business workflows using event-driven patterns on Apache Kafka for client processing activities, exception escalation, SLA monitoring, and lifecycle state machines for Investor Services operations.
  • Build AI-powered features in the Investor Services Workbench, including LLM-driven intelligent assistance, NLP-powered search and query across Investor Services data, and RAG-based knowledge tools that surface contextual insights in the user interface.
  • Design clean, versioned REST and GraphQL APIs for the client portal and internal consumers, ensuring contracts are documented, backward-compatible, and aligned with Investor Services canonical data models.
  • Improve engineering quality through code reviews, pairing sessions, architecture discussions, and knowledge sharing, particularly on AI tooling adoption, domain-driven design, and clean-code practices.
  • Champion engineering excellence by writing unit, integration, and contract tests; instrumenting observability with OpenTelemetry; conducting chaos-engineering experiments; and maintaining five-nines operational standards.

About the Company

Citi

Runs banking and payments for global clients

Citi runs banking, investment and payment services for companies, governments and individuals around the world. Its global network connects institutions with local banking systems, while its US consumer business sells credit cards and deposit accounts. Corporate clients use Citi to manage cash, finance trade and raise capital, and investors use its trading, custody and wealth services to hold and manage assets. The bank earns interest on loans and fees from payments, securities transactions, financial advice and account services. Citi traces its banking roots to 1812; the Citigroup holding company was formed in 1998, and its headquarters are in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1812

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