Software Engineer, Full Stack

Instalily.Ai•San Francisco, NY

3d•$150,000 - $190,000•Hybrid

About The Position

As a Full Stack Software Engineer at InstaLILY, you'll own meaningful pieces of our AI agent platform: the core systems that let autonomous agents reason, act, and integrate into our enterprise customers' workflows. You'll work alongside the Lead Software Engineer and a team drawn from top-tier programs to design, build, and ship the platform features that show up in production at our customers. You'll work across the stack, from backend services and agent infrastructure to APIs and the web interfaces our customers actually touch. This role is deeply client-facing. You won't be coding in a vacuum and handing off to a customer success team. You'll be in the room with our customers from the start. You'll sit in working sessions with enterprise stakeholders, run technical discovery, translate messy real-world workflows into shipped features, and embed with customer teams during rollouts. The best engineers here are the ones who can switch between writing production code in the morning and walking a Fortune 500 VP through a system architecture in the afternoon. You need to code at a high bar, make architectural decisions you can defend, and explain them clearly to people who don't speak engineer.

Requirements

Bachelor's or Master's in CS, engineering, math, physics, or related: demonstrated ability matters more than credential
3–5 years of experience as a software engineer, with a track record of shipping production systems across the full stack
Strong fluency on the backend (Python, TypeScript, or similar) and the frontend (React, Next.js, modern TypeScript)
Solid grasp of system design fundamentals (API design, data modeling, async patterns, caching, queues) and frontend architecture (component design, state management, performance)
Production experience with cloud infrastructure (AWS, GCP, or Azure) and CI/CD pipelines
AI-serious: you've built and shipped something real with LLMs (a production RAG system, an agent in customer hands, a non-trivial integration), and you have opinions on what works and what doesn't
Comfortable in front of customers: you can run a technical discovery session, defend an architectural decision to a non-technical exec, and translate vague enterprise requirements into something concrete
Strong written and verbal communication: you can write a clear design doc, send a clean customer-facing update, and present to a room without disappearing into jargon

Nice To Haves

Experience mentoring junior engineers, leading technical reviews, or owning a meaningful surface of a codebase
Prior experience in a forward-deployed, solutions engineering, or client-embedded role at a B2B software company
GCP
Vercel
Temporal
Alembic
Docker
Prior experience with third-party / enterprise system integrations

Responsibilities

Own end-to-end design and delivery of features across the full stack: backend services, agent infrastructure, APIs, and customer-facing web UIs
Build, ship, and operate LLM-powered systems: agents, RAG pipelines, tool-use frameworks, evaluation harnesses, and the supporting infrastructure that makes them reliable in production
Lead technical discovery with new enterprise customers; sit with their teams, map their workflows, and translate what you hear into shipped product
Embed with customer teams during deployments and rollouts; be the engineering presence in the room, not the one waiting for a Jira ticket
Present architecture and technical tradeoffs to non-technical executives at our customers, and defend them under pressure
Partner with the Growth team to turn customer feedback into roadmap; iterate on what's actually being used vs. what we thought would be useful
Raise quality and reliability across the codebase through comprehensive testing, code review, and CI/CD practices
Mentor junior engineers: pair on hard problems, review their code thoughtfully, and help them level up
Contribute to architectural discussions and technical reviews; help shape how we build as we scale
Stay current on AI/ML and software engineering trends, and bring back what's worth adopting