Senior Software Engineer, Virta Health

• Strong backend engineering skills, with a track record of building and operating scalable, reliable systems in production — ideally involving APIs, event-driven architectures, or data integrations
• A proactive, ownership-first mindset — you don’t wait for direction; you surface problems, propose solutions, and drive them to completion
• High agency and autonomy — able to navigate ambiguity, set direction, and execute independently, while keeping stakeholders aligned
• Experience with B2B or partner-facing data systems, such as file-based integrations, real-time data exchanges, or partner APIs
• Comfort working in fast loops, using experimentation and the Build-Measure-Learn mindset to validate assumptions and continuously improve outcomes
• Willingness to leverage AI tools and patterns — not just as a curiosity, but as a practical way to enhance velocity, observability, and quality
• Strong collaboration and communication skills, especially in cross-functional environments involving product, data, and external partners
• Help define technical strategy and influence roadmaps across partner and platform teams to align near-term work with long-term goals
• Typically 7–10 years of software engineering experience, with demonstrated ability to operate at a senior level

Desirable

• This role is a unique blend of real-world impact, technical challenge, and cutting-edge tools
• You’ll help build and evolve Virta’s data engagement platform — the system that powers how we exchange critical healthcare data with our partners
• You'll directly influence workflows like Coverage Eligibility, which determines whether someone can access life-changing care, and Member Marketing, which ensures the right people hear about Virta at the right time
• You’ll move beyond brittle file drops and manual processes, designing modern, partner-friendly APIs and automation-first workflows — all while tapping into the power of AI to boost observability, accelerate development, and create smarter systems
• This isn’t a role where AI is just a buzzword
• You’ll actually get to integrate AI into your solutions — from streamlining onboarding, to improving data quality, to auto-generating documentation, alerts, or test cases
• If you're excited about shaping foundational infrastructure, working cross-functionally, and using AI to build cleaner, faster, more intelligent systems, this is a place where you can thrive
• Design and implement core components of Virta’s data exchange and engagement platform, enabling scalable, reliable, and partner-friendly data integrations
• Lead technical discovery and delivery of high-impact projects across use cases like Coverage Eligibility and Member Marketing, collaborating closely with product, data, and external partners
• Apply Lean Principles and an experiment mindset to drive progress through rapid iterations — using the Build-Measure-Learn loop to validate assumptions, reduce risk, and focus on outcomes over output
• Modernize legacy systems, transitioning from file-based processes to API- and event-driven architectures, while ensuring strong observability, resilience, and security
• Leverage AI tools and techniques to streamline workflows, enhance data quality, and accelerate development — including testing, documentation, and operational insights
• Own systems end-to-end — from architecture through operations — and actively identify opportunities to improve platform performance, partner experience, and long-term maintainability
• First 30 Days: Learn & Connect
• Understand Virta’s data ecosystem — architecture, key data flows, systems for Coverage Eligibility and Member Marketing, and how partners interact with Virta’s platform
• Get familiar with existing processes and pain points around file-based exchanges, partner onboarding, and incident patterns
• Build relationships with key stakeholders: engineering teammates, product managers, data team, and partner-facing roles (like Solutions or Support)
• Observe real-world partner data issues, reviewing tickets, Slack threads, and postmortems to identify recurring themes
• Days 31–60: Contribute & Experiment
• Ship production code: contribute meaningfully to an in-flight initiative, ideally touching data flows or partner integrations
• Identify and propose a small experiment or improvement, using the Build-Measure-Learn loop — e.g. , automating a partner data quality check, or prototyping an API-first replacement for a file drop
• Leverage AI in your workflow (e.g. , for test generation, observability enhancements, or documentation)
• Start building technical credibility across the team by writing clean, scalable code and actively participating in design reviews
• Days 61–90: Lead & Shape
• Own a meaningful workstream — such as a small net-new service, a platform capability (e.g. , data validation or status tracking), or a cleanup/migration effort
• Drive an architectural discussion that involves tradeoffs across scalability, observability, and partner UX
• Show thought leadership by pushing forward better patterns (e.g. , eventing over polling, AI-powered tooling, test coverage strategies)
• Build trust through delivery — others should be seeking your input and starting to rely on you as a technical thought partner