We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorganChase within the Chief Technology Office (cto)Enterprise Observability Platforms team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
Executes software solutions across design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build cloud and platform solutions and break down complex technical problems (including AWS infrastructure, Kubernetes, and hybrid integration).
Creates secure and high-quality production code and maintains algorithms/services that run synchronously with appropriate systems, including containerized runtimes on AWS.
Architects, builds, and maintains production infrastructure in AWS using Terraform, including secure-by-design provisioning, change management, and lifecycle operations for core services.
Manages, optimizes, and scales containerized environments leveraging AWS EKS/Kubernetes (and related orchestration, networking, load balancing, IAM/security, autoscaling, and production troubleshooting).
Develops backend automation tools, lightweight microservices, and internal APIs to streamline platform operations and infrastructure lifecycle management across cloud and hybrid environments.
Enhances observability, resilience, and throughput for high-volume enterprise telemetry/observability data pipelines running in the cloud; proactively identifies hidden problems and patterns in data to improve coding hygiene and system architecture.
Produces architecture and design artifacts for complex applications, ensuring design constraints are met by software code development; gathers, analyzes, synthesizes, and develops visualizations/reporting from large, diverse data sets in service of continuous improvement.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 3+ years applied experience.
Hands-on practical experience in system design, application development, testing, and operational stability, including production support for cloud-hosted services.
Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages, with emphasis on platform/infrastructure automation.
AWS architecture & core services — hands-on experience building in AWS with services like VPC, EKS, IAM, S3, Lambda, CloudWatch, KMS, ALB/NLB, Auto Scaling.
Hands-on experience deploying and operating containerized workloads on AWS ECS and/or EKS, including service orchestration, networking/load balancing, IAM/security, autoscaling, and troubleshooting in production.
AWS networking — VPC design (subnets, route tables, NAT/IGW), security groups/NACLs, PrivateLink/VPC endpoints, hybrid connectivity concepts (VPN/Direct Connect), DNS (Route 53).
Terraform — authoring reusable modules, workspaces, remote state/backends, state management, imports, lifecycle/meta-arguments, dependency design, and troubleshooting plans/applies for AWS resources.
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation), validating and refining outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Overall knowledge of the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Solid understanding of agile methodologies such as CI/CD, application resiliency, and security; partners effectively with on-premises platform engineers to ensure seamless hybrid transport and integration across environments.
Preferred qualifications, capabilities, and skills
Familiarity with messaging systems like Confluent Kafka and AWS MSK and related components such as Kafka Streams, Connect, and Schema Registry. Confluent Kafka and AWS MSK and related components such as Kafka Streams, Connect, and Schema Registry.
Familiarity with building/operating streaming and telemetry pipeline systems (e.g., Kafka/MSK-based) to support high-throughput observability data ingestion, processing, and delivery.
Originally posted on Himalayas