Founding Solutions Engineer Enterprise

Overview

Job title: Founding Developer Evangelist / Solutions Engineer - (Enterprise)

Location: London; full in-office working as default

Start date: ASAP

Reports to: CTO, with dotted line to CRO and CEO

Compensation: £60k–£90k base (potential to go higher depending on experience) plus equity

At Cosine, we’re building autonomous AI engineers that plan, write, and ship code inside real development workflows. Cosine is designed for on-premise and virtual private cloud (VPC) deployments, including fully air-gapped environments. We build our agent tooling entirely in-house and post-train open-source models to deliver reliable, enterprise-grade coding performance in security-critical settings. In 2024, Cosine achieved a 72% score on OpenAI’s SWE-Lancer benchmark, placing us among the strongest real-world software-engineering AI systems evaluated.

YC-backed and well-funded, Cosine was founded by experienced operators focused on building dependable, production-grade AI.

This role is based in our Hoxton office, five days a week, because close collaboration, fast feedback, and shared context matter for the problems we’re solving.

At Cosine, enterprise adoption depends on technical trust. Autonomous agents are still poorly understood, often oversold, and rarely inspected with the rigour serious engineering teams require.

We are hiring a Founding Developer Evangelist to make Cosine’s technology legible, credible, and evaluable to the world’s most sophisticated engineering teams.

This Role Sits At The Intersection Of

• Deep technical understanding (agents, ML systems, evals, infrastructure)
• Enterprise-facing technical communication
• Hands-on support for real-world evaluations and pilots

Content creation is a core tool, but not the end goal. The goal is to help enterprises understand, trust, and safely evaluate Cosine
.

• Support enterprise evaluations and pilots (core responsibility)
• Act as a technical counterpart to enterprise engineering teams during evaluations, pilots, and early deployments
• Join architecture reviews, technical deep dives, and security-focused conversations
• Explain how Cosine works in practice: its agent architecture, training approach, evaluation methods, and operational constraints
• Help teams understand where Cosine excels, where it currently has limits, and how to evaluate it responsibly
• Identify repeated technical objections, points of confusion, and failure modes encountered during real-world evaluations
• Create best-in-class technical content (informed by reality)
• Produce long-form technical explainers grounded in real evaluation learnings:
  • Agent architecture and control
  • Evaluation methods (correctness, reliability, long-horizon behaviour)
  • Training approaches and research insights
  • Security, auditability, and on-prem deployment
• Translate research-level concepts into content that CTOs, Staff+ engineers, and technical evaluators can reason about
• Create clear diagrams, walkthroughs, and examples that help engineers form accurate mental models
• Produce high-quality video content where it meaningfully increases clarity or trust
• Own Cosine’s technical narrative (enterprise-first)
• Develop a coherent, technically rigorous narrative for how Cosine differs from:
  • “AI wrappers”
  • Code assistants
  • Narrow benchmark-driven tools
• Ensure Cosine is understood as:
  • A research-driven ML lab
  • A production-grade autonomous agent platform
• Maintain a consistent voice that emphasises credibility, honesty, and depth, especially for regulated enterprises
• Capture and feed back real-world technical insights
• Systematically capture insights from enterprise evaluations, including:
  • Where teams get stuck
  • What they distrust
  • Which evals matter most to them
  • What blocks internal approval
• Share structured feedback with product, research, and engineering teams.
• Help shape documentation, evals, and product priorities based on repeated patterns observed in the field.
• Produce early technical case studies and evaluation write-ups
• Create technically rigorous case studies based on pilots and early deployments
• Focus on what was tested, how it was evaluated, what worked, and what didn’t

• Enterprise…