Staff Software Engineer

Invoca is hiring a Staff Software Engineer to improve a critical stage of its engineering lifecycle and help teams build and operate AI-powered products. The role focuses on creating measurable gains in engineering speed, quality, safety, and business impact through domain leadership, shared practices and tools, and responsible adoption of AI workflows.

Responsibilities:

• Take end-to-end accountability for a critical stage of Invoca's engineering lifecycle in your domain, whether that's reliability, security, data, quality, delivery, customer deployment, or architecture
• Define what “great” looks like in your domain and hold the bar, rather than waiting for it to be defined for you
• Identify where AI and agentic workflows can meaningfully improve your domain: faster incident detection, smarter test generation, automated security review, adaptive data pipelines, self-healing deployments, or similar
• Establish safe, observable, and auditable ways to bring AI into your workflows, and help the teams around you adopt them with confidence
• Build shared practices, tooling, or platforms in your domain that every team can adopt, replacing one-off, team-specific approaches
• Treat your domain as a product with internal users: define adoption goals and measure whether teams are actually better off because of your work
• Translate technical decisions in your domain into terms leadership and product teams care about: velocity, cost, risk, customer trust, and revenue impact
• Partner with engineering and product leadership to prioritize your work based on measurable business and customer impact, not technical elegance alone
• Drive direction and standards across multiple teams in your area of expertise
• Influence decisions through clarity, judgment, and evidence, and act as a trusted advisor to engineering and product leadership

Requirements:

• 5+ years of experience (Senior) or 8+ years of experience (Staff) with deep expertise in your engineering specialization, with a track record of measurable impact in production environments
• Experience building systems, tools, or practices that were adopted broadly because they demonstrably improved speed, quality, or safety
• Curiosity about AI and agentic workflows, and a track record of practically applying new tools rather than just being interested in them
• Strong technical judgment with a bias toward simplicity and adoption over theoretical completeness
• Ability to connect technical work to business and customer outcomes, and to communicate that connection clearly
• Experience partnering across engineering, product, and business functions
• High ownership mindset, curiosity, and urgency in a fast-moving, evolving technical environment