Lead Python Backend Engineer - AWS API

JPMorgan Chase

Plano (TX)

On-site

USD 150,000 - 190,000

Full time

5 days ago

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Job summary

JPMorgan Chase in Plano, TX seeks a Lead Software Engineer to join an agile team delivering trusted market-leading technology products in a secure, scalable way. You will design, build, and run AWS cloud-native microservices, lead AI-assisted engineering practices, implement IaC, CI/CD, and observability, and mentor colleagues across product/platform disciplines.

This role emphasizes production-grade code, secure coding, incident RCA, and collaboration with SRE, security, and data teams to drive

Qualifications

Formal training or certification on software engineering concepts and 5+ years applied experience.
Design AWS cloud-native architectures (microservices, event-driven, serverless) meeting availability/latency/DR targets
Build Python backend services (FastAPI/Flask): API design, validation, downstream integrations
Deliver serverless workloads on AWS (Lambda + API Gateway/EventBridge/Step Functions) with IAM scoping, concurrency, and tuning
Containerize and deploy to ECS/Fargate and/or EKS with sizing, autoscaling, and rollout strategies
Design and operate data stores (RDS/Aurora, DynamoDB) including schema/indexing/partitioning and performance optimization
Use caching (ElastiCache/Redis) to optimize throughput/latency under load
Own CI/CD (CodePipeline/CodeBuild/CodeDeploy and/or GitHub Actions) with automated tests and quality gates
Implement observability + reliability (CloudWatch, X-Ray/OpenTelemetry), SLIs/SLOs, alerting, incident response/RCA
Enforce AWS security/compliance: least-privilege IAM, KMS, secrets (Secrets Manager/SSM), VPC patterns, CloudTrail/Config/GuardDuty/Security Hub, and audit support

Responsibilities

Execute creative software solutions through design, development, and troubleshooting to solve complex technical problems.
Deliver end-to-end AWS cloud-native, microservices-based applications using Python and modern engineering best practices.
Design, build, and evolve distributed systems on AWS using Lambda, ECS/Fargate, and/or EKS aligned to scalability, performance, and cost needs.
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Apply domain modeling to structure business products for clarity, testability, and continuous evolution.
Develop secure, high-quality production code; perform thorough code reviews; debug and remediate issues in others' code.
Build and maintain AWS infrastructure with IaC (Terraform/CloudFormation) for repeatable, auditable deployments.
Implement/enhance CI/CD with automated testing and reliable release patterns (blue/green, canary, rollback) for zero-downtime where required.
Build resiliency + observability (multi-AZ, decoupling, retries/timeouts, idempotency, circuit breakers; logging/metrics/tracing/alerting via CloudWatch/X-Ray/OpenTelemetry).
Operate and improve production: investigate incidents, lead RCA, prevent recurrence by automating remediation, optimize data stores (Aurora/RDS, DynamoDB, S3), and modernize dependencies while collaborating across product/platform/SRE/security/data and mentoring inclusively.