Staff Software Engineer
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Job Description
Staff Software Engineer leading cross-team platform delivery and AI-native engineering practices at Pathstream. Building reliable systems that help frontline employees advance their careers.
Responsibilities:
- Lead large, cross-team technical work on Pathstream's platform as a senior individual contributor
- Act as an expert in owned systems and understand data flows across the platform
- Lead multi-person projects from design through production
- Set the technical bar for the engineering pod and help engineers grow
- Own team delivery with AI and improve project scoping, sequencing, staffing, and throughput
- Maintain shared AI patterns, including context files, skills, conventions, and workflows
- Lead adoption of Claude Code, Claude skills, MCP servers, AI code review, and other AI tools
- Improve verification practices through test strategy, staged rollout, and observability
- Lead large feature releases and solve complex engineering problems across team boundaries
- Break complex initiatives into maintainable pieces and guide trade-offs
- Write architecture documents and review technical documents
- Drive quality, security, SOC2, vulnerability management, and enterprise controls
- Conduct thorough, helpful code reviews and improve incident detection, prevention, and response
- Mentor engineers, collaborate with product, design, and cross-functional partners, influence hiring, and develop engineering talent
Requirements:
- 7+ years of professional software engineering experience, with a strong track record as a senior engineer
- Expert in one or more technical areas and proficient across a broad range of others
- Experience leading projects across team boundaries and shipping systems other engineers depend on
- Deep familiarity with Ruby on Rails, React, JavaScript/TypeScript, Python, Docker, PostgreSQL, and AWS
- Practical experience operating production systems that hold customer data, including security and compliance work in a SaaS environment
- AI is a core part of current work, with examples of how it changed software scoping, building, and review
- Experience building AI tooling such as skills, MCP servers, context files, evaluation harnesses, or multi-step agentic workflows, with adoption by other engineers
- Experience shipping AI features in production systems where an LLM is a first-class component, including evaluation, observability, and cost management
- Ability to verify AI output rigorously and identify failure modes and checks
- Authorized to work for any employer in the U.S.; employment visa sponsorship is unavailable
- Ability to lead through influence, handle ambiguity, make data-informed decisions, stay calm under pressure, seek feedback, and act on it
Benefits:
- Transparent and social culture, challenging work, fast learning cycles, practical training, and meaningful feedback
- Strong sense of ownership and strategic work that impacts our product, users, colleagues, business, and world
- 100% employer-paid medical, dental, and vision for you; 50% for partner/spouse and dependents
- Health, commuter, and parking flexible spending accounts
- Employee Assistance Program (mental health, financial health, legal support)
- Free access to wellbeing apps (Ginger, Headspace)
- Flexible paid time off and paid holidays
- Generous paid parental leave
- Short and long-term disability insurance
- Annual professional development budget
- Company-provided laptop
- Remote-first culture
- Life insurance (100% company paid)
- 401(k)
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