InstaLILY
Software Engineer, Full Stack
$150K–$190K
New York, New York, United States, San Francisco, California, United States +2 · Full-time · Posted Jun 13, 2026
- Location
- New York, New York, United States, San Francisco, California, United States
New York, New York, United States
San Francisco, California, United States - Experience
- 3–5 years as a software engineer.
- Education
- Bachelor's or Master's in CS, engineering, math, physics, or related; demonstrated ability matters more than credential.
About the job
Own and deliver full-stack features for an enterprise AI agent platform, working directly with customers to translate workflows into production software.
What you'll do
- Design, build, operate, and improve full-stack platform features, including LLM agents, RAG pipelines, APIs, and customer-facing interfaces.
- Lead customer discovery and deployments; translate enterprise workflows into shipped features and explain technical decisions to stakeholders.
- Improve reliability through testing, code review, and CI/CD; mentor engineers and contribute to architecture and roadmap decisions.
What they ask for
- 3–5 years of software engineering experience shipping production systems across the full stack.
- Fluency in backend development with Python, TypeScript, or similar, and frontend development with React, Next.js, and modern TypeScript.
- Production experience with cloud infrastructure and CI/CD; solid system design and frontend architecture fundamentals.
- Bachelor's or Master's in CS, engineering, math, physics, or related; demonstrated ability matters more than credential. Experience building and shipping real LLM-powered systems and comfort leading customer discussions are also required.
Nice to have
- Experience mentoring junior engineers, leading technical reviews, or owning a meaningful codebase area.
- Experience in a forward-deployed, solutions engineering, or client-embedded B2B software role.
Pay
$150,000–$190,000 USD per year, base salary
Tools
TypeScript, React, Next.js, Python, FastAPI, SQLAlchemy, PostgreSQL, GCP
AI focus
Build and operate LLM-powered agents, RAG pipelines, tool-use frameworks, evaluation harnesses, and supporting production infrastructure.
Model-written summary · the original posting is authoritative