Senior Lead Software Engineer -Java/Kotlin , Python programmer, APIs

About this role

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Skills you'll use

What you'll do

• Design and develop scalable, fault-tolerant microservices and APIs that support rule-based and ML-based detection pipelines, evaluating performance and cost trade-offs.Model and implement supervision and reviewer workflows using state machines (alert triage, queues, escalations, dispositions).
• Build streaming and batch data pipelines that ingest, index, and enrich communications content and the alerts generated on that content, with APIs for upstream and downstream integrations.
• Design data models for Alerts, Queues, Policies, and audit artifacts, ensuring immutability, lineage, and full traceability for audits.
• Operationalize ML and LLM models into detection and alert-generation pipelines in partnership with Data Science and ML Engineering.
• Build robust unit, integration, and performance tests aligned to an ideal test pyramid, following Test-Driven Development.
• Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.
• Build CI/CD pipelines with automated quality-control gates across the delivery lifecycle and implement observability hooks - metrics, tracing, and logging, to reduce production toil through proactive monitoring and troubleshooting.
• Partner with product management and compliance SMEs to monitor and improve the accuracy, reliability, and false-positive rates of generated alerts.
• Proactively identify hidden problems and patterns in communications data and use those insights to improve detection quality and drive product and process improvements.

Who can apply

• 8+ years building resilient, scalable, cost-efficient, enterprise-grade cloud-native products, with 2+ years in compliance for the financial industry.
• Expert Java/Kotlin and Python programmer with experience building headless, externally consumable APIs.
• Experience building cloud-native microservices for streaming and batch architectures using Spark and/or Flink.
• Well versed with AWS services, including but not limited to EC2, ECS, EKS, EMR, S3, and Glacier and hands-on with Elastic/OpenSearch, Kafka, and PostgreSQL and experience integrating and operationalizing ML/LLM models and pipelines in production.
• Hands-on with AI productivity tools such as GitHub Copilot and Qodo (Codium).
• Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns.
• Experience with observability and monitoring tools such as Prometheus, Grafana, and OpenTelemetry.
• Experience building CI/CD pipelines using ArgoCD, Helm, Terraform, Jenkins, and GitHub Actions.
• Prior experience in Test-Driven Development, delivering products with well-defined SLI/SLO/SLAs and strong ownership mentality with excellent communication skills and a collaborative mindset.

About JPMorgan Chase

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