Responsibilities
The Associate Software Development Engineer is a broad engineering role that spans the full spectrum from application development to delivery infrastructure
This role contributes to the EPM product itself — writing backend services, APIs, and tooling — while also building and maintaining the CI/CD pipelines, cloud infrastructure, and automation that keep the platform running reliably
Rather than specializing narrowly in infrastructure or application code, this role is expected to move fluidly across both, using AI tooling to operate effectively across that wider surface area
Contribute to EPM product development, including backend services, APIs, and data-layer work, writing code that is clean, tested, and maintainable
Build and maintain CI/CD pipelines that enable fast, reliable delivery of product changes across EPM components
Provision and manage cloud infrastructure using infrastructure-as-code, following team standards for security, reliability, and cost
Develop internal tooling and automation that reduces toil and improves the productivity of the broader engineering team
Support monitoring, alerting, and observability tooling so engineering teams have clear, actionable signal on system and application health
Participate in incident response, contributing to root cause analysis and follow-up improvements across both platform and application layers
Use AI tooling as a standard part of the development workflow — for code generation, infrastructure configuration, troubleshooting, test coverage, and documentation
Collaborate across Engineering, Product, and Security to understand delivery needs and surface gaps early
Maintain clear documentation for platform components, APIs, and operational procedures
Success Criteria
Product code contributions are clean, tested, and ship with confidence through the delivery pipeline
CI/CD pipelines are reliable and changes move through the delivery process without unnecessary friction
Infrastructure is provisioned through code, consistently and repeatably, without manual intervention
Internal tooling and automation reduce toil measurably over time rather than accumulating as permanent overhead
Platform and application issues are detected through monitoring before they become customer-facing incidents
AI tools are used routinely and effectively across both development and platform work, improving output speed and quality
Hands‑on use of AI tools (such as GitHub Copilot, Claude, or similar) across development and infrastructure work — not as a novelty but as a routine productivity practice.
Qualifications
Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience; 2+ years of professional software engineering experience spanning application development and delivery infrastructure
Hands‑on experience with cloud infrastructure (AWS, Azure, or GCP) and infrastructure‑as‑code tools such as Terraform or Pulumi
Scripting and automation proficiency in Python, Bash, or similar, applied to both operational tasks and developer tooling
Working knowledge of containerization and orchestration, including Docker and Kubernetes
Clear written communication skills and a collaborative working style across Engineering, Product, and Security
Familiarity with monitoring and observability tooling such as Datadog, Prometheus, Grafana, or equivalent
Experience building or contributing to CI/CD pipelines using tools such as GitHub Actions, Jenkins, GitLab CI, or equivalent
Proficiency in at least one backend language (Python, Java, Go, C#, or similar) with experience writing production‑quality services or APIs
Exposure to front‑end development (TypeScript, React, or similar) sufficient to contribute across the full stack
Familiarity with GitOps workflows and tools such as ArgoCD or Flux
Experience with event‑driven architectures or message queue systems (Kafka, RabbitMQ, or similar)
Prior experience in a SaaS or cloud‑native product engineering environment
Exposure to secrets management solutions such as HashiCorp Vault or cloud-native equivalents
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The Associate Software Development Engineer is a broad engineering role that spans the full spectrum from application development to delivery infrastructure
This role contributes to the EPM product itself — writing backend services, APIs, and tooling — while also building and maintaining the CI/CD pipelines, cloud infrastructure, and automation that keep the platform running reliably
Rather than specializing narrowly in infrastructure or application code, this role is expected to move fluidly across both, using AI tooling to operate effectively across that wider surface area
Contribute to EPM product development, including backend services, APIs, and data-layer work, writing code that is clean, tested, and maintainable
Build and maintain CI/CD pipelines that enable fast, reliable delivery of product changes across EPM components
Provision and manage cloud infrastructure using infrastructure-as-code, following team standards for security, reliability, and cost
Develop internal tooling and automation that reduces toil and improves the productivity of the broader engineering team
Support monitoring, alerting, and observability tooling so engineering teams have clear, actionable signal on system and application health
Participate in incident response, contributing to root cause analysis and follow-up improvements across both platform and application layers
Use AI tooling as a standard part of the development workflow — for code generation, infrastructure configuration, troubleshooting, test coverage, and documentation
Collaborate across Engineering, Product, and Security to understand delivery needs and surface gaps early
Maintain clear documentation for platform components, APIs, and operational procedures
Success Criteria
Product code contributions are clean, tested, and ship with confidence through the delivery pipeline
CI/CD pipelines are reliable and changes move through the delivery process without unnecessary friction
Infrastructure is provisioned through code, consistently and repeatably, without manual intervention
Internal tooling and automation reduce toil measurably over time rather than accumulating as permanent overhead
Platform and application issues are detected through monitoring before they become customer-facing incidents
AI tools are used routinely and effectively across both development and platform work, improving output speed and quality
Hands‑on use of AI tools (such as GitHub Copilot, Claude, or similar) across development and infrastructure work — not as a novelty but as a routine productivity practice.
Qualifications
Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience; 2+ years of professional software engineering experience spanning application development and delivery infrastructure
Hands‑on experience with cloud infrastructure (AWS, Azure, or GCP) and infrastructure‑as‑code tools such as Terraform or Pulumi
Scripting and automation proficiency in Python, Bash, or similar, applied to both operational tasks and developer tooling
Working knowledge of containerization and orchestration, including Docker and Kubernetes
Clear written communication skills and a collaborative working style across Engineering, Product, and Security
Familiarity with monitoring and observability tooling such as Datadog, Prometheus, Grafana, or equivalent
Experience building or contributing to CI/CD pipelines using tools such as GitHub Actions, Jenkins, GitLab CI, or equivalent
Proficiency in at least one backend language (Python, Java, Go, C#, or similar) with experience writing production‑quality services or APIs
Exposure to front‑end development (TypeScript, React, or similar) sufficient to contribute across the full stack
Familiarity with GitOps workflows and tools such as ArgoCD or Flux
Experience with event‑driven architectures or message queue systems (Kafka, RabbitMQ, or similar)
Prior experience in a SaaS or cloud‑native product engineering environment
Exposure to secrets management solutions such as HashiCorp Vault or cloud-native equivalents
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