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Sobre este puesto de Software Engineer en Compeer Financial

Compeer Financial · Híbrido · IL-Bloomington, WI-Sun Prairie

Empowered to live. Inspired to work.
Compeer Financial is a member-owned cooperative located in Illinois, Minnesota and Wisconsin. We bring together team members with a variety of backgrounds and experiences to help provide financial services to support agriculture and rural communities. Join us in a culture that not only promotes meaningful work and professional development, but provides a flexible, hybrid work environment and excellent benefits, which empower you to thrive both personally and professionally.

How we support you:

  • Hybrid model – up to 50% work from home
  • Flexible schedules including ample flexibility in the summer months
  • Up to 9% towards 401k (3% fixed Compeer contribution plus up to 6% match)
  • Benefits: medical, dental, vision, HSA/FSA, life & AD&D insurance, short-term and long-term disability, wellness program & EAP
  • Vacation, sick leave, holidays/floating holidays, parental leave, and volunteer paid time off
  • Learning and development programs
  • Mentorship programs
  • Cross-functional committee opportunities (i.e. Inclusion Council, emerging professional groups, etc.)
  • Professional membership/certification reimbursement and more!

Casual/seasonal & intern team members are not eligible for benefits except for state-mandated programs.

To learn more about Compeer Financial visit www.compeer.com/careers. 

This position offers a hybrid work option up to 50% remote and is based out of the Sun Prairie, WI or Bloomington, IL office location.

The contributions you will make: 

This position independently designs, develops, tests, deploys, operates, and improves secure, reliable, maintainable software solutions. Working within a cross-functional product team, this role owns features and moderately complex outcomes from refinement through production, translates product and technical requirements into effective designs and implementations, and makes sound engineering decisions within established architecture and standards. Applies proficient knowledge of the team's programming languages, frameworks, APIs, data patterns, automated testing, CI/CD, cloud-native engineering, observability, DevSecOps, and production support practices; diagnoses moderately complex defects and operational issues; and evaluates trade-offs involving quality, security, performance, reliability, maintainability, and cost. Responsibly applies AI-enabled engineering tools, Agentic AI patterns, and AI agents to improve productivity and solution quality. Contributes technical judgment to team decisions, supports less-experienced engineers, and connects engineering choices to product objectives, client needs, operational risk, and business value.

A typical day: 

  • Owns software engineering delivery by independently owning features and moderately complex software outcomes from refinement through production. Clarifies technical requirements, decomposes work, designs and implements components and integrations, writes and maintains automated tests, deploys changes, monitors production behavior, and resolves defects. Makes sound implementation decisions within established architecture and remains accountable for security, quality, reliability, performance, maintainability, supportability, accessibility, and completion of assigned outcomes.
  • Advances technical mastery and engineering judgment by applying proficient knowledge of the team's programming languages, frameworks, APIs, data access and integration patterns, development tools, and software lifecycle. Designs cohesive components using established architecture and design principles; evaluates implementation options and trade-offs; applies automated testing, debugging, CI/CD, cloud-native, observability, DevSecOps, and production engineering practices; and learns unfamiliar technologies or domain concepts as needed to solve moderately complex problems. Responsibly applies AI-enabled engineering tools and practices, Agentic AI patterns, and AI agents for coding, testing, analysis, documentation, and automation while critically validating outputs, protecting sensitive information, maintaining human accountability, and exercising sound engineering judgment.
  • Connects engineering to business outcomes by understanding product goals, client needs, business processes, acceptance criteria, operational expectations, and risk relevant to owned outcomes. Refines requirements with product and business partners, identifies technical implications and constraints, evaluates practical trade-offs, and recommends implementation options that balance delivery needs with sustainable engineering. Operates as a trusted, value-added partner by communicating clearly, bringing technically informed recommendations, and following through on commitments.
  • Strengthens Engineering Quality and Team Effectiveness by actively shaping technical design discussions, code reviews, automated testing, deployment readiness, incident response, root-cause analysis, documentation, and continuous improvement for owned work. Identifies design, quality, maintainability, reliability, security, and operational concerns; improves test coverage and observability; helps resolve delivery or production impediments; and contributes reusable practices that improve team effectiveness and software quality.
  • Collaborate across teams by working across software and quality engineering, product, architecture, platform, UX, security, data, operations, and business teams to deliver integrated outcomes. Communicates technical decisions, dependencies, risks, and trade-offs clearly; incorporates relevant perspectives; coordinates dependencies; constructively challenges assumptions when evidence warrants; and helps resolve issues that cross 
    component or team boundaries.
  • Builds team capability and supports others by sharing engineering knowledge, providing useful review feedback, supporting less tenured engineers and peers, maintaining reusable documentation, and seeking coaching when needed. Continues to expand technical and domain expertise, applies feedback and evidence to improve decisions, and demonstrates accountability, curiosity, trust, resilience, and constructive collaboration while building the depth and leadership capability required for more complex technical ownership.

The skills and experience we prefer you have: 

  • Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or a related technical discipline; or an equivalent combination of education and experience.
  • Professional knowledge of software engineering principles, data structures, algorithms, software design, debugging, automated testing, and the software development lifecycle.
  • Professional experience designing, developing, testing, deploying, or supporting production software using modern programming languages, frameworks, and software engineering practices.
  • Experience independently delivering software features or comparable technical outcomes using a modern programming language, Git-based source control, automated testing, and continuous integration and delivery practices.
  • Experience analyzing moderately complex software problems, making and communicating implementation or design decisions, evaluating technical trade-offs, and applying secure development, reliability, observability, and quality engineering practices.
  • Experience designing or operating cloud-native, API-based, event-driven, distributed, or data intensive application components, preferred.
  • Experience with APIs, relational or non-relational data stores, integration patterns, and production troubleshooting, preferred.
  • Experience with CI/CD, DevSecOps, observability, automated testing, or production support practices, preferred.
  • Experience responsibly applying AI-enabled engineering tools and practices, Agentic AI patterns, AI agents, or intelligent automation throughout the software development lifecycle, preferred.
  • Ability to independently design and deliver features, components, integrations, and moderately complex software outcomes using established architecture and engineering patterns and produce clean, maintainable, appropriately documented, and well-tested code through production.
  • Ability to analyze and resolve moderately complex software and production problems by using code, logs, metrics, traces, debugging tools, and systematic problem solving to identify root causes, evaluate alternatives, implement durable fixes, and escalate systemic or high-risk concerns appropriately.
  • Ability to apply software design principles to define component responsibilities, interfaces, APIs, data models, dependencies, and error-handling approaches; evaluate implementation trade-offs; and make sound design decisions within established architecture, security, and engineering standards.
  • Ability to independently use source control, automated testing, build and deployment pipelines, observability, development environments, and delivery tools to move changes safely through the software lifecycle and support them in production.
  • Ability to responsibly apply AI-enabled engineering tools and practices, Agentic AI patterns, and AI agents to coding, testing, analysis, documentation, and automation while evaluating generated approaches, validating outputs, protecting sensitive information, maintaining human accountability, and upholding engineering standards.
  • Ability to communicate technical designs, implementation choices, defects, dependencies, risks, and trade-offs effectively with technical and non-technical partners; clarify requirements; provide informed recommendations; incorporate feedback; and build trust through reliable follow-through.
  • Ability to independently decompose and organize moderately complex work, estimate and communicate progress, coordinate dependencies, adapt to changing priorities, contribute meaningful code and design reviews, and help improve testing, documentation, operational readiness, and team delivery practices.
  •  Advanced knowledge in one or more areas relevant to the team's software, such as application architecture, cloud-native development, APIs and integration, data persistence, distributed systems, security, or performance, preferred.
  • Working knowledge of infrastructure automation, DevSecOps, observability, platform engineering, or production reliability practices, preferred.
  • Understanding of financial services, agriculture, or other regulated industries, preferred.
  • Proficiency with one or more modern programming languages and application development frameworks used by the team, preferred.

#IND100

How we will take care of you:

Our job titles may span more than one career level (associate, senior, principal, etc.). The actual title and base pay offered is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role is eligible for variable compensation and other benefits.

Base Pay
$84,400—$127,700 USD

Compeer Financial is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.

Must be authorized to work for any employer in the United States. Compeer is unable to sponsor or take over sponsorship of an employment visa at this time.

Click here to view federal employment laws applicable for applicants.

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Cómo se compara este salario de Software Engineer

Este puesto paga $106,050/yr — por debajo de el rango típico para los puestos de Software Engineer.

$98,800 la mediana de $175,000 $260,000

Rango típico $133,992–$216,775/yr, a partir de 10,882 ofertas comparables de Software Engineer en JobsRadar (salario anualizado en USD). Ver datos salariales de Software Engineer →

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