Merciv is building the intelligence layer for enterprise commerce. We connect an organization's entire data landscape — internal systems, social signals, industry reports, consumer behavior — and surface the insights and automated workflows that used to take analysts weeks. We raised $14M in seed funding, spent two years in stealth building the right thing, and we're now launching publicly. Our platform already drives 8-figure gross margin improvements for some of the world's largest retailers. We're a lean, high-ownership team. If you want to see your work matter immediately, this is it. The Role You'll build the core systems powering Merciv's agentic infrastructure — the data pipelines, APIs, and distributed services that enterprise clients depend on daily. This isn't a "contribute to a team" role. You own features from architecture to production. You'll work closely with ML/AI engineers, product, and designers. The problems are hard, the surface area is real, and the impact is visible. What You'll Do • Design and scale backend services in Go and Python powering real-time autonomous intelligence for Fortune 500 clients • Architect data ingestion pipelines that handle millions of points across internal and external sources • Build APIs that serve our agentic AI platform at enterprise scale • Collaborate with ML/AI engineers to ship predictive models into production • Own system reliability — fault tolerance, observability, performance under load • Shape architectural decisions that define the long-term trajectory of the platform • Mentor engineers and raise the bar for backend engineering as we grow • You have 5+ years of backend engineering experience building systems at scale • You're deeply proficient in Go and/or Python, with strong distributed systems fundamentals • You've worked with both SQL and NoSQL databases and know how to process data at scale • You've run production systems on Kubernetes • You think in systems — you can design for performance, scalability, and maintainability at once • You thrive on ambiguity and hard problems, not just well-scoped tickets • Former technical founders are encouraged to apply — we care more about what you've built than how long you've been building