JPMorganChase
Website:
jpmorganchase.com
Company:
https://www.linkedin.com/company/jpmorganchase
Seniority: Not Applicable
Industries: Financial Services
Job details:
Job Description
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. We are building a next-generation, AI-driven, cloud-native Supervision & Surveillance product that monitors enterprise digital communications for compliance violations, misconduct, and policy breaches at massive scale.
As a Sr. Software Engineer/Lead Engineer at JPMorgan Chase within the digital communications compliance team, you will design and implement core backend services, streaming pipelines, and data flows that power our detection logic, alert triage, reviewer workflows, and explainable audit trails. You will work across billions of communications and content events, collaborating with product managers, architects, data science, platform, and operations teams, while engaging with engineering communities to explore new and emerging technologies.
Job Responsibilities
- 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.
Required Qualifications, Capabilities, And Skills
- 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.
- Experience mentoring engineers and providing technical leadership at a senior level.
Preferred Qualifications, Capabilities, And Skills
- Familiarity with modern front-end technologies and MLOps in the cloud, strom is a plus.
- Experience building cost models aligned to SLIs/SLOs.
- Exposure to data privacy, PII handling, and encryption in a regulated environment.
ABOUT US
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