General Intelligence Company
About the role
At General Intelligence Company, we’re building highly-capable autonomous agents for startups. Our goal is to enable the
one-person, one-billion-dollar company.
Our agents don’t just automate workflows - they replace them. We're looking for a researcher to lead our applied AI team to work towards our goal of fully autonomous businesses. What you’ll do
Design and run experiments across model selection, prompting, tool-use, memory, planning, and multi-agent coordination
Lead evaluations: build datasets, success criteria, and continuous benchmarks for real workflows
Push performance: reduce tail latency and failure modes; improve determinism, throughput, and cost per successful run
Partner with eng/product to ship weekly
Mentor a small, senior team; set standards for experiment design, code quality, and documentation
Push state-of-the-art results on custom agent systems
Pursue advanced memory research for multi agent systems
What you’ve done
5–8+ years in applied ML/AI, ML systems, or research engineering; high-ownership startup experience preferred
Deep experience with LLMs and agentic systems: prompting, function/tool calling, planning, retrieval/memory, evals
Track record moving paper → prototype → production (Python; comfort with distributed systems a plus)
Published papers in AI/ML that are directly applicable to modern agentic systems
Built reliable evaluation harnesses and curated datasets for multi-step tasks
Shipped improvements that moved core business metrics (success rate, latency, unit economics)
Bonus: orchestration frameworks, streaming/real-time state sync, safety/guardrails, reinforcement/online eval loops
How we work
In-person in New York; high autonomy; ship fast; iterate daily
Small team, zero politics; you own outcomes end-to-end
Heavy use of modern AI tooling (Cursor, structured outputs, eval pipelines)
High performance team working on the most interesting problems in agents.
What’s Different About GIC?
No bureaucracy.
We hire smart, high-agency people and let them work.
Real ownership.
You won’t just push tickets—you’ll shape the product.
Small, elite team.
Work directly with founders and have a major impact.
Craft matters.
Speed is key, but quality is never sacrificed.
In person, in New York City.
#J-18808-Ljbffr
At General Intelligence Company, we’re building highly-capable autonomous agents for startups. Our goal is to enable the
one-person, one-billion-dollar company.
Our agents don’t just automate workflows - they replace them. We're looking for a researcher to lead our applied AI team to work towards our goal of fully autonomous businesses. What you’ll do
Design and run experiments across model selection, prompting, tool-use, memory, planning, and multi-agent coordination
Lead evaluations: build datasets, success criteria, and continuous benchmarks for real workflows
Push performance: reduce tail latency and failure modes; improve determinism, throughput, and cost per successful run
Partner with eng/product to ship weekly
Mentor a small, senior team; set standards for experiment design, code quality, and documentation
Push state-of-the-art results on custom agent systems
Pursue advanced memory research for multi agent systems
What you’ve done
5–8+ years in applied ML/AI, ML systems, or research engineering; high-ownership startup experience preferred
Deep experience with LLMs and agentic systems: prompting, function/tool calling, planning, retrieval/memory, evals
Track record moving paper → prototype → production (Python; comfort with distributed systems a plus)
Published papers in AI/ML that are directly applicable to modern agentic systems
Built reliable evaluation harnesses and curated datasets for multi-step tasks
Shipped improvements that moved core business metrics (success rate, latency, unit economics)
Bonus: orchestration frameworks, streaming/real-time state sync, safety/guardrails, reinforcement/online eval loops
How we work
In-person in New York; high autonomy; ship fast; iterate daily
Small team, zero politics; you own outcomes end-to-end
Heavy use of modern AI tooling (Cursor, structured outputs, eval pipelines)
High performance team working on the most interesting problems in agents.
What’s Different About GIC?
No bureaucracy.
We hire smart, high-agency people and let them work.
Real ownership.
You won’t just push tickets—you’ll shape the product.
Small, elite team.
Work directly with founders and have a major impact.
Craft matters.
Speed is key, but quality is never sacrificed.
In person, in New York City.
#J-18808-Ljbffr