Full-Stack SaaS Engineering :
- Design, build, and operate modern SaaS web applications end to end (frontend, backend, APIs, database, integrations)
- Deliver production-grade features that span UI, data, and infrastructure, from prototype to resilient MVP
- Integrate common SaaS services (e.g. Stripe, Supabase, auth, analytics) to accelerate delivery
- Balance speed and simplicity with reliability, scalability, and compliance
AI Product Engineering :
Leverage AI in your own workflow to code faster, explore solutions, and sharpen ideasAdd AI functionality into our SaaS products : LLM-driven features, retrieval-augmented workflows, agentic patterns, and evaluation / guardrailsInstrument systems for observability; track latency, accuracy, and usage metrics to ensure safe and reliable AI behaviorApply evaluation datasets and guardrails; implement abstain / escalation flows and drift monitoring to uphold qualityFrontend Craft :
Build tasteful, intuitive UIs in frameworks like Next.js, even when a designer isn't availableUse good product judgment to make interfaces feel polished, purposeful, and usableUphold accessibility, performance, and compliance standardsProduct Delivery :
Translate high-level technical direction into executable designs and production code, surfacing trade-offs earlyOwn vertical slices : integrate with internal systems and external services, de-risk unknowns with spikes, and ship on a tight cadenceCo-lead execution with the Tech Lead, driving toward MVP milestones and team KPIs (reliability, adoption, impact)Architecture & Collaboration :
Evolve flexible, composable architectures that interoperate with partner platforms and internal servicesCommunicate design decisions and trade-offs clearly with technical and non-technical stakeholdersLearning & Thought Partnership :
Stay ahead of AI and software trends, bringing pragmatic tools and frameworks into the stackShare learnings and patterns that increase team velocity and qualityContinuously find ways to accelerate our AI-assisted product developmentAbout You
You are a hands-on product engineer with a strong track record of shipping modern SaaS web applications end to end. You thrive on building products that are both technically solid and delightful to use, and you're just as comfortable designing a UI flow as you are modeling a database schema or hardening a backend service. You actively use AI in your own workflow and know how to responsibly integrate LLMs and agentic techniques into production-grade products. You're curious, pragmatic, and excited to apply your skills to climate tech with real-world impact.
You bring the following skills and mindset to the role :
Technical & Product Engineering :
Track record of shipping full-stack SaaS applications (frontend, backend, APIs, data, integrations) used in production by real usersAbility to go from zero to prototype quickly, then harden into a resilient MVP with tests, telemetry, and safe deployment practicesStrong fundamentals across APIs, data modeling, security, performance, CI / CD, and observabilityExperience integrating LLMs, RAG, and guardrails into products, and monitoring AI features with metrics like latency, accuracy, and safetyComfort making trade-offs that balance time-to-value with reliability, security, and data integrityEvidence of shortening the loop from idea → prototype → production, with telemetry guiding iterationProduct Taste & Frontend Craft :
Strong eye for design and user experience; able to create polished, usable UIs without always relying on a dedicated designerKnowledge of modern frameworks like Next.js and comfort working across the modern SaaS stack (e.g., Stripe, Supabase, auth, analytics, cloud services)Domain & Collaboration :
Interest in climate, energy, or environmental markets, with the ability to translate domain input into dependable softwareClear, proactive communicator who builds trust with engineers, product managers, and subject-matter experts alikeComfortable moving at startup velocity inside an established company, adapting quickly as requirements evolveEducation & Experience :
Degree in Computer Science / Software Engineering or equivalent practical experience building and operating full-stack, AI-enabled SaaS products