Senior Full Stack Engineer – AI

PeopleConnect Staffing

1d•$140,000 - $180,000•Remote

About The Position

Our client is building AI that connects people with others who've achieved similar goals. Their unique platform helps users find mentors, peers, and guides based on shared experiences—not just keywords. They are a lean, AI-native team. They don't scale by adding headcount. They scale by shipping faster with better tools. If you've built features in an afternoon that used to take a sprint, you'll fit right in. You'll be the technical owner of the entire stack. Not a "lead" managing a growing team—an owner who ships, architects, and multiplies output through AI agents and a small bench of specialist contractors. This role is for someone who already treats Claude, Cursor, and Copilot as their default development environment. Someone who's experimented with agentic workflows—not as a novelty, but because it's faster. You'll report to the Head of Product and work directly with the founders and customers.

Requirements

5+ years building production systems across frontend and backend
Strong in TypeScript/JavaScript and Python
Hands-on experience with GCP (Vertex AI, Cloud Run, BigQuery) or equivalent
Production experience integrating LLM APIs (Anthropic, OpenAI, Google)
Comfortable with PostgreSQL, Redis, and event-driven patterns
You already use AI coding assistants daily—not experimentally, habitually
You've built or experimented with agentic workflows (LangGraph, CrewAI, custom orchestration)
You think in terms of "what can I delegate to an agent?" before "what do I need to build?"
You're curious about prompt engineering, evals, and AI reliability—not just AI hype
You've owned systems end-to-end, not just contributed to them
You're comfortable making architecture decisions without a committee
You know when to ship fast and when to slow down for quality
You communicate clearly in writing—specs, PRs, async updates
Experience working with or managing contractors/freelancers
Ability to write clear specs that enable autonomous work
Comfort giving direct feedback on code quality and deliverables
No ego about where good code comes from—human or AI

Responsibilities

Full ownership of their GCP/Vertex AI infrastructure, APIs, and frontend
Architecture decisions that will scale from dozens to thousands of users
Production reliability, deployment pipelines, and technical debt management
Security, compliance, and data integrity across all systems
Define deliverables for specialist contractors (frontend, DevOps, ML)
Review PRs from both humans and AI-generated code
Build and maintain our internal agentic workflows—treating AI agents as asynchronous team members
Document patterns so contractors and agents can work autonomously against clear specs
Pioneer their "1 dev × N agents" operating model
Build reusable prompts, agent configs, and automation scaffolding
Establish workflows where AI handles first drafts, boilerplate, tests, and docs—you handle architecture, edge cases, and judgment calls
Continuously evaluate new AI dev tools and integrate what works
Audit and document the current stack; identify tech debt and quick wins
Establish CI/CD and deployment workflows optimized for rapid iteration
Ship at least one customer-facing feature end-to-end
Build the contractor onboarding playbook (specs, PR standards, async communication)
Implement at least one agentic workflow that measurably accelerates development