Harnham
Lead Software Engineer - Applied AI
Skills
10 days ago
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Important information
Contract type:
Permanent
Salary:
$250,000 – $350,000 / year
Location:
New York, NY, USA
Work mode:
Remote
Published on:
14 October 2026
What they need
Lead Software Engineer - Applid AI | Second in Command to the CTO
Remote, East Coast preferred | Up to $350k total comp + equity
The company
A profitable, fast-growing AI company spun out of a leading quant-backed investment firm, working with some of the largest private equity firms in the world (around $1T in combined assets). They build a digital twin of an organisation, simulating its people, processes and systems to show where AI can drive growth and efficiency.
AI for good
They don’t walk into a business and say cut 30% of your staff and replace them with AI. They use the digital twin to find opportunities for growth and efficiency, with AI working alongside people to improve what they already do. It’s a mission the whole team believes in, and they welcome healthy debate on AI, sceptics included.
The role
- Be the CTO’s right hand and technical number two
- Own the development of the digital twin platform, from architecture through to production
- Stay hands-on, building LLM systems in Python across OpenAI, Anthropic and Gemini (LangChain/LangGraph, RAG, agentic workflows, evals)
- Run on GCP (BigQuery, Cloud Run, CI/CD) with no big DevOps team behind you
- Support and mentor the engineers and analysts around you as the team scales
You’ll bring
- 8+ years in software engineering, with real production LLM work
- Strong Python and cloud data experience
- A builder’s mindset, ideally from a small, scrappy team or startup
- Clear communication with non-technical stakeholders
- Bonus: PE or finance exposure (easily learned on the job)
Why now
- Team has doubled in six months, with Series A expected shortly
- Greenfield build, so you choose the tools
- Early equity before the next round is priced
- A product used directly in engagements with top-tier PE clients
Process: screen, technical interview (take-home where AI tools are encouraged, followed by a walkthrough of your decisions), team conversations, then a final meeting with the founder.
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