Top Software Engineer Jobs in Portland, OR

Staff Software Engineer responsible for technical strategy, architecture, complex feature design, implementation, scalability, and greenfield development. The role mentors engineers, leads design and code reviews, drives technical alignment, addresses technical debt, participates in hiring, and remains a hands-on contributor to full-stack enterprise software development using technologies such as PHP, Laravel, Vue.js, and MySQL.

Lead enterprise automation architecture and delivery across RPA, workflow automation, process mining, intelligent automation, testing, bots, citizen development, and AI orchestration. Establish and operate an Automation Center of Excellence, identify high-value use cases, guide implementation, manage governance and regulatory alignment, support training and adoption, and track financial value. Work hands-on with business stakeholders, technology teams, vendors, and external consultants in a regulated life sciences environment.

Build and maintain Hospitable’s core and growth platform using Laravel, PHP, MySQL, Angular, and Kubernetes. Develop customer-focused features, shape product decisions, improve performance, debug production issues, refactor code, and implement observability and testing practices. Collaborate with product, sales, customer success, and engineering teams in a remote distributed environment. The role emphasizes maintainable software, customer value, independent decision-making, and AI-assisted development using tools such as Cursor.

Build and scale Daymark Health’s cancer care platform across the stack. Responsibilities include developing secure infrastructure and core systems, collaborating with product, data, operations, and customers, integrating workflows, following HIPAA and SOC 2 controls, handling PHI securely, and using AI coding tools to accelerate development. The role requires contributing to technical strategy, improving user experience, and adapting quickly in a startup environment.

Build and operate reliable backend systems and APIs for high-traffic products. Responsibilities include distributed system design, data modeling, service architecture, performance tuning, automated testing, observability, incident management, and end-to-end feature delivery. The role partners with Product and Design, makes architecture decisions, mentors engineers, and applies AI-assisted development tools responsibly.

Designs, develops, implements, tests, and maintains PTC Windchill PLM solutions and ThingWorx integrations for Department of Defense customers. Leads architecture, customization, data migration, enterprise integration, testing, troubleshooting, documentation, training, and end-user support while managing a small technical team. Requires expertise in Windchill architecture, development, migration methodologies, SQL, Java, security configuration, and related enterprise technologies.

Own customer outcomes from discovery through production deployment. Build decision systems using ontologies, reasoning, graph analytics, optimization, and machine learning over enterprise data. Write Python, SQL, and PyRel; debug unfamiliar systems; tune performance; harden deployments; document reusable solutions; and upstream platform improvements. Lead technical workshops and proofs of concept while partnering closely with customers, Product, and Engineering.

Own end-to-end supplier integrations: design, implement, test, and monitor third-party APIs. Ship weekly, improve tooling and abstractions, ensure reliability, and mentor peers. Use AI-assisted workflows to speed integration development.

Build scalable simulation and planning systems for complex communications networks. Model hypothetical scenarios, allow users to vary configurations and assumptions, evaluate impacts, compare tradeoffs, identify risks, and integrate simulation capabilities into broader product workflows. The role involves full-stack engineering across design, development, testing, and operations, with emphasis on distributed systems, algorithms, network modeling, and computational reliability.

Build and operate AI agent systems with customer engineering teams, helping move prototypes into reliable production systems. Design agents, improve evaluations, monitoring, scaling, and reliability, and train customers on the Mastra framework. Translate recurring customer challenges into open-source framework improvements, fix performance issues, ship new primitives, improve code quality, and influence the product roadmap through production insights.