Staff Software Engineer

About Nectar We're living through a fundamental shift in how people discover, evaluate, and purchase products. The next generation doesn't respond to traditional marketing. They build relationships with brands through authentic social interactions, seek recommendations from communities they trust, and expect personalized experiences that feel human, not corporate. At Nectar, we're building the AI-native social operating system that enables this new era of commerce. We believe every social interaction should deepen the relationship between brands and their communities while creating genuine value for both sides. Our AI agents listen in real time, surface actionable insights, attribute engagement to revenue, and turn conversations into conversions. Founded by ex-Meta product and engineering leaders, we work with brands like OLIPOP, Hatch, K18, Little Spoon, and many more. We hit product-market fit last year and are on a fast growth trajectory – the business has grown 10x in the past year, and we're hiring to keep up with customer demand. The Role We're looking for a Staff Software Engineer to build and scale Nectar’s core product experiences and platform. You'll work across the full stack from the backend infrastructure that ingests and processes large volumes of social data, to the product interfaces that help brands understand, manage, and respond to social conversations using AI. This role combines deep engineering with technical leadership. Whether you lean more toward backend systems or product/frontend, you'll shape architectural decisions, raise the quality bar across the codebase, and help establish strong engineering practices as the team and platform scale. Our tech stack is TypeScript, React, Shadcn, Zustand, AWS, Pulumi, Postgres, ClickHouse, and Turbopuffer. We use AI tools thoughtfully in our day-to-day work – Cursor, Claude Code, Graphite, and Granola. What You'll Be Doing Backend & Data Infrastructure Design and build backend systems that ingest and process large volumes of social data from platforms like Instagram, TikTok, X, and LinkedIn Develop resilient integrations with third-party APIs and optimize the infrastructure that powers our AI workloads Improve reliability, performance, and cost efficiency across our backend and data pipelines as the platform scales Establish operational best practices including monitoring, incident response, and on-call culture Product & Frontend Build AI-powered product experiences such as conversation inboxes, AI-suggested replies, and summarization of social conversations into actionable insights Improve shared components, design systems, and frontend architecture to enable faster and higher-quality product development Optimize performance and reliability across the application as it scales to support thousands of daily users Collaborate closely with product and design teams to deliver intuitive workflows for brand and marketing teams Technical Leadership Write architecture documents and guide infrastructure, tooling, and frontend decisions across the engineering team Review technical designs and code from other engineers - providing feedback that raises the quality bar across the team Mentor engineers and contribute to building strong engineering culture and development practices What We're Looking For Strong engineering experience designing, building, and operating production systems — backend, frontend, or full-stack Deep understanding of system design, distributed systems, and scalable architecture Experience building reliable data pipelines on top of external APIs, or building complex, data-rich web applications using React Strong user empathy and product intuition when designing and building features Experience mentoring engineers and shaping engineering culture Curiosity about how AI is changing software development and interest in AI-assisted engineering workflows Comfort operating in a fast-moving startup environment with high ownership and end-to-end responsibility Bonus Points Experience working with high-scale data pipelines or real-time data processing systems Experience building AI-powered user interfaces or LLM-integrated product features Experience building analytics dashboards or data-heavy interfaces Experience integrating AI or machine learning systems into production environments Previous experience working at an early-stage or rapidly scaling startup