How does swipeandhired work?

You set your target roles, salary floor and locations once. swipeandhired scores matching postings against your profile, drafts tailored application materials with AI, and either lets you swipe to apply, one tap at a time, or runs fully on autopilot. Every application is tracked in your dashboard.

Which ATS platforms does swipeandhired support?

All of them. swipeandhired applies on every applicant tracking system (ATS) employers use, including Workday, SmartRecruiters, Greenhouse, iCIMS, Lever, Ashby, Taleo, SuccessFactors, Oracle Cloud and Jobvite, and on a company's own careers page when it uses none of them. You can also bring any posting yourself by link or pasted text.

Can I cancel my subscription?

Anytime, in one click from the billing portal in Settings. Your plan stays active until the end of the current billing period. No retention calls, no dark patterns.

Is my data used for training AI models?

Our platform AI provider may use the content we send it, your profile and the job posting, to improve its models. We never sell your data. If you bring your own AI provider key, requests go directly to your provider under their terms.

SRE Software Engineer III at JPMorgan Chase, Jersey City, NJ

SRE Software Engineer III at JPMorgan Chase in Jersey City, NJ. Est. up to $200k. Apply with swipeandhired.

Build technology that powers critical business outcomes at JPMorganChase. Join a collaborative engineering team where you can grow your skills, strengthen reliability at scale, and help deliver resilient customer experiences.

As an SRE Software Engineer III at JPMorganChase within Corporate Technology, you will build and operate resilient software solutions that improve availability, scalability, and customer experience. You will collaborate across engineering and stakeholder groups to design automated delivery approaches, apply site reliability principles, and resolve complex issues before they impact users.

Job Responsibilities

Design and implement automated continuous integration and continuous delivery pipelines to improve release quality, speed, and repeatability

Develop, test, and deliver software solutions that strengthen availability, reliability, scalability, and operational readiness of applications and services

Partner with engineers, technical experts, and key stakeholders to troubleshoot and resolve complex, multi-system problems to restore service and prevent recurrence

Define and use service level indicators and service level objectives to proactively identify risk, prioritize reliability improvements, and reduce customer impact

Advance observability practices by improving telemetry, dashboards, and alerting to shorten time-to-detect and time-to-recover

Improve operational excellence through runbooks, automation, and continuous improvement actions that reduce toil and production risk

Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.

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.

Required Qualifications, Capabilities, and Skills

Formal training or certification on software engineering concepts and 3+ years applied experience

Proficiency in site reliability culture and principles, including applying reliability practices within an application or platform

Proficiency in at least one programming language such as Python, Java/Spring Boot, or.NET

Experience building observability solutions, including telemetry collection and service level objective-based alerting using tools such as Grafana, Dynatrace, Prometheus, Datadog, or Splunk

Experience with continuous integration and continuous delivery tools such as Jenkins, GitLab, or Terraform

Familiarity with containers and orchestration technologies such as Docker, Kubernetes, or Amazon Elastic Container Service

Working knowledge of diagnosing and troubleshooting common networking concepts and issues in distributed systems

Ability to proactively remove blockers, learn new technologies, and apply new approaches to improve delivery outcomes

Working knowledge of using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated 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.

Preferred Qualifications, Capabilities, and Skills

Experience designing reliability improvements using error budgets, capacity planning, and resilience patterns (e.g., rate limiting, backpressure, graceful degradation)

Experience improving release safety with progressive delivery practices (e.g., canary deployments, feature flags, automated rollbacks)

Experience implementing automated quality gates (unit, integration, performance, and security testing) within delivery pipelines

Exposure to incident management practices, post-incident reviews, and implementing measurable remediation actions to prevent recurrence

Familiarity with infrastructure-as-code and standardized environment provisioning to improve consistency and auditability