Apps Dev Tech Sr Lead Analyst

Apps Development Group Manager

Trade Manager Zone Platform | Cash Securities Settlements | Equity Growth Initiative

Level: C14

About the Role

We are looking for an experiencedApps Development Group Manager to lead engineering for theTrade Manager Zone (TMZ) platform within theCash Securities Settlements group, supporting theEquity Growth Initiative. This is a senior engineering leadership role that combineshands-on technical contribution with organizational accountability — you will be expected to stay close to the code and architecture while also owning the platform strategy, engineering standards, and team development across multiple squads.

You will be responsible for the reliability, scalability, security, and evolution of a mission-critical equity settlement platform, and will play an active role in embeddingAI and ML capabilities into both the platform and the engineering workflow.

Key Responsibilities

1. Hands-On Technical Leadership & System Design

• Actively participate in system design, architecture reviews, and code reviews across TMZ platform teams.
• Contribute to the design ofdistributed, fault-tolerant, real-time systems for high-volume, low-latency equity trade processing.
• Write, review, and refactorproduction-grade code in Kotlin, Java, and Python — setting the technical bar for the team.
• Lead design ofevent-driven, microservices-based architectures using Kafka or Solace — including message schema design, topic partitioning, consumer group strategies, and fault-tolerant processing.
• Drivelow-latency and high-performance system design — leading performance profiling, bottleneck analysis, and optimization of critical platform components.
• Design and governdata architecture across Oracle (SQL) and MongoDB (NoSQL) — schema design, indexing strategies, query optimization, and data consistency patterns.
• Championtrunk-based development, feature flags, and progressive delivery — contributing to CI/CD pipeline design and optimization.
• Produce and reviewarchitecture decision records (ADRs) and technical design documents for key platform components.

2. AI & ML Integration — Technical & Strategic

• Contribute hands-on toAI/ML integration on the TMZ platform — designing AI pipelines, evaluating ML frameworks, and reviewing AI model integration code.
• Lead the implementation ofAI-powered platform capabilities — intelligent exception handling, predictive settlement failure detection, anomaly detection on trade flows, and automated reconciliation.
• Evaluate and adoptGenAI and LLM APIs — prototyping and architecting capabilities such as natural language interfaces for trade operations, AI-driven exception summarization, and GenAI-powered operational tooling.
• Use and promoteAI-assisted development tools (e.g., GitHub Copilot or equivalent) — driving team adoption and establishing best practices for AI-augmented engineering.
• Lead the design ofAI/ML pipelines on real-time trade event streams — working with data engineers and ML practitioners on feature engineering, model serving, and inference architecture.
• Define and enforceAI governance standards — responsible AI practices, model explainability, auditability, and regulatory compliance.
• Identify and prioritizeAI adoption opportunities across the platform — focusing on high-value, engineering-led use cases.

3. Engineering Excellence & Quality

• Set and enforceengineering standards across all TMZ teams — TDD, BDD, trunk-based development, CI/CD, secure coding, and observability.
• Conductcode reviews on critical platform components — providing detailed technical feedback that improves team capability over time.
• Drive adoption ofAI-powered quality practices — predictive quality analytics, AI-augmented code review, and automated test generation.
• Leadperformance engineering — profiling JVM-based applications (Kotlin/Java), identifying hotspots, and optimizing critical settlement processing paths.
• Own thesecurity and compliance posture of the TMZ platform — involvement in threat modeling, vulnerability assessments, and secure design reviews.
• Defineengineering metrics and KPIs — DORA metrics, test coverage, MTTR, and platform SLIs — using data to drive continuous improvement.
• Ensure all engineering delivery is aligned toCiti Engineering Excellence Standards — CI/CD, DevOps, cloud-native practices, and modern ways of working.

4. Platform Strategy & Domain Ownership

• Define and own theengineering roadmap for the Trade Manager Zone platform, aligned to the Equity Growth Initiative and Cash Securities Settlements objectives.
• Develop strongdomain knowledge in equity trade lifecycle, settlement mechanics, and cash securities processing to inform sound engineering decisions.
• Own the platform'sSLA, SLO, and SLI commitments — driving architectural decisions to meet availability, throughput, and latency targets.
• Leadcross-platform integration — governing API contracts, data flows, and system dependencies across the Cash Securities Settlements ecosystem.
• Drivecapacity planning and investment prioritization — decisions on platform scaling, technology refresh, and resource allocation.
• Partner withOperations, Risk, Compliance, and Business teams to ensure the platform meets regulatory requirements and business needs.

5. People Leadership & Team Development

• Lead and developmultiple engineering teams — building a culture of technical quality, accountability, and continuous learning.
• Own thetalent strategy for TMZ engineering — hiring, retaining, and developing engineers with expertise in financial systems, modern engineering, and AI/ML.
• Develop thenext generation of technical leads and engineering managers within the organization.
• Mentor senior engineers and managers — providing technical coaching, architecture guidance, and career development support.
• DriveAI upskilling across the team — building capability in AI tooling, prompt engineering, and responsible AI through direct mentorship and practical workshops.

6. Stakeholder Engagement

• Act as theprimary engineering point of contact for the TMZ platform with senior business, technology, and operations stakeholders.
• Communicateplatform health, delivery progress, engineering strategy, and risk clearly to senior leadership.
• Partner withProduct, Operations, Risk, Finance, and Compliance to align engineering priorities with business and regulatory needs.
• Represent TMZ engineering incross-business technology forums and architecture councils.
• Managevendor and partner relationships relevant to the platform — cloud providers, tooling vendors, and AI/ML partners.

Skills and Qualifications

Must-Have Skills

1. Programming — Hands-On Proficiency

• Kotlin  Primary platform language — strong hands-on proficiency; write, review, and architect production-grade Kotlin services
• Python  Hands-on expertise in data pipelines, AI/ML integration, scripting, and automation
• Java  Extensive hands-on experience in high-throughput, production-grade Java engineering; JVM performance tuning

2. System Architecture — Real-Time, High-Throughput & Performance

• Microservices Architecture Hands-on design of microservices ecosystems — service decomposition, API design, inter-service communication
• Event-Driven & Messaging Systems  Deep hands-on expertise inKafka orSolace — topic design, partitioning, consumer groups, exactly-once semantics, high-throughput stream processing
• Low-Latency & High-Performance Computing Hands-on profiling and optimization — JVM tuning, GC optimization, thread management, memory profiling
• High Availability & Fault Tolerance  Hands-on design of resilience patterns — circuit breakers, bulkheads, failover, and disaster recovery 
• Databases  Hands-on expertise inOracle (SQL) — schema design, query optimization, indexing — andMongoDB (NoSQL) — document modeling, aggregation pipelines, sharding, replica sets

3. Advanced Data & AI Integration

• AI & ML Integration Hands-on experience designing and integrating AI/ML models — model serving, inference pipelines, real-time scoring, feature engineering 
• GenAI & LLM Integration Hands-on experience with GenAI tooling and LLM APIs — prototyping, evaluating, and productionizing GenAI capabilities
• Data Engineering  Hands-on expertise in data pipelines, streaming data processing (Kafka Streams, Flink, or equivalent), and data quality patterns 
• Intelligent Automation  Hands-on application of ML to automate exception handling, anomaly detection, and operational workflows
• AI Governance  Establishing AI governance standards — explain ability, auditability, bias mitigation, and regulatory compliance

4. Cloud & DevOps — Citi Engineering Excellence Standards

• Cloud-Native Engineering  Hands-on experience withAWS, Kubernetes, and Docker — container orchestration, autoscaling, and cloud-native deployment 
• CI/CD & DevOps  Hands-on design and ownership of CI/CD pipelines aligned to Citi Engineering Excellence Standards
• Observability & AIOps  Hands-on experience with distributed tracing, intelligent alerting, and AI-driven observability
• Secure Engineering  Hands-on threat modeling, vulnerability assessments, and secure design reviews
• Agile at Scale Agile/SAFe delivery at program level — PI planning, cross-team dependency management, delivery governance

Good-to-Have Skills

• Hands-on experience withreal-time ML model serving — feature stores, online inference, and model monitoring.
• Familiarity withRAG patterns, vector databases (e.g., Pinecone, Weaviate), or agentic AI frameworks (e.g., LangChain, AutoGen).
• Knowledge ofMLOps practices — model versioning, deployment pipelines, and production model monitoring.
• Understanding ofregulatory compliance frameworks relevant to securities settlement (e.g., T+1, CSDR).
• Experience withchaos engineering and resilience testing — fault injection and production readiness reviews.
• Knowledge ofreconciliation and exception handling patterns in settlement workflows.
• Familiarity withprompt engineering and LLM fine-tuning in an enterprise, regulated context.
• Experience withtechnology investment governance and engineering budget management.

What We Are Looking For

• Stays hands-on — actively contributes to design, code reviews, and technical problem-solving alongside the team.
• Operates at two levels — comfortable working at the code and architecture level while owning platform strategy and stakeholder relationships.
• Pragmatic about AI — identifies practical, high-value opportunities to apply AI/ML without losing focus on engineering fundamentals.
• Accountable for outcomes — takes ownership of platform quality, reliability, and delivery across the organization.
• Develops people — invests in engineers and managers, building technical capability and leadership depth across the team.
• Communicates clearly — able to translate technical complexity into clear, concise updates for business and senior leadership audiences.

Why Join Us

• Lead engineering for a platform central to global equity trade settlement operations — while staying technically engaged.
• Drive AI and engineering transformation as part of the Equity Growth Initiative, with senior visibility and business impact.
• Work at the intersection of high-throughput financial systems and modern AI capabilities.
• Build and develop a strong engineering team with access to good tooling, platforms, and talent.
• Be part of an engineering culture that values technical depth at every level of seniority.

Education:

• Bachelor’s degree/University degree or equivalent experience
• Master’s degree preferred

Cash Securities Settlements | Trade Manager Zone Platform | Equity Growth Initiative | C14

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