Engineering Manager (Agentic Engineering)

1 нед. назад

94k–141k GBP / yearUnited KingdomEuropeLeadRemote

goreacttypescriptllmapi

Lead and grow a software engineering team developing agentic systems and developer experiences.

Будет плюсом

(Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!)
Experience building coding agents, developer tools, or cloud development environments.
Experience with MCP, agent tools, or multi-agent systems.
Experience with remote execution, sandboxing, or isolated compute.
Experience building abstractions across multiple model providers.
Deep experience with AWS, Kubernetes, Docker, or Linux.
Open-source contributions or experience working directly with customers.

Как откликнуться

We believe that the interview process should be transparent, consistent, and enjoyable. We value your time and hope to complete the interview process in two to four weeks, if schedules allow. Through your interviews, you will meet a mix of individual contributors, managers, and senior leaders.
As an AI company, embraces the use of AI tools, and we want to be transparent about our expectations as you navigate our interview process.
Not permitted : Using AI assistance during conversational interviews.
Permitted : Using AI tooling for take-home assessments. Please flag where and to what extent it was used in your take-home. Your submission will not be penalized for using AI as long as it is done honestly.

Другое

As an Engineering Manager on ’s Agentic Engineering team, you’ll lead engineers building and evolving the systems behind our agentic development experience. You’ll help make agents more capable, reliable, and useful across real development environments.
You’ll guide technical direction, grow the team, and keep execution sharp. You’ll work closely with Engineering, Product, and Design across the agent harness, integrations, and developer workflows.
Lead and grow a team within our Agentic Engineering organization.
Set technical direction across the agent harness, integrations, and workflows.
Stay close to the code and contribute to architecture and implementation decisions.
Evolve agent execution, tool use, context management, streaming, and long-running workflows.
Extend our provider-agnostic architecture as models and capabilities change.
Partner with Product and Design to turn agent capabilities into useful developer experiences.
Improve reliability, performance, and operability across agentic systems.
Coach engineers, raise the technical bar, and create clarity around priorities and tradeoffs.
Experience managing and growing software engineering teams.
Strong hands-on engineering experience with Go.
Experience with React and TypeScript.
Hands-on experience building systems around LLMs and agentic workflows.
Experience with model APIs, tool calling, context management, or agent loops.
Strong distributed systems knowledge.
Working knowledge of AWS.
Strong technical judgment and comfort working through ambiguity.
A track record of helping engineers grow while maintaining a high execution bar.
Backend: Go, Postgres
Frontend: TypeScript, React
Infrastructure: AWS, Kubernetes
Observability: Prometheus, Grafana
CI/CD: GitHub Actions
’s agentic architecture is provider-agnostic. The foundation is built; this team is focused on making it more capable, reliable, and extensible as the space evolves.
is the leading platform for AI development Infrastructure, enabling enterprises to securely run human and AI-driven development workflows in consistent, governed environments. provides self-hosted, agent-ready workspaces that unify developer productivity and platform governance. With , enterprises can confidently evolve from human-only development to AI-assisted and autonomous workflows, without sacrificing security, compliance, or performance. Learn more at .com .
We use AI tools to help manage our recruitment process efficiently and fairly. Specifically:
Ashby helps us review inbound applications by surfacing candidates who best match the role requirements we've defined. This tool does not make hiring decisions; it helps our team prioritize which applications to review first.
Granola takes notes during our interview calls so our team can focus on the conversation with you.
All hiring decisions are made by humans. Our team reviews applications, conducts interviews, and makes final selections. AI tools assist us but never replace human judgment, and these practices are conducted in compliance with applicable data protection, AI governance, and labor laws. Your data is not used to train AI models.
In accordance with New York City Local Law 144, an independent bias audit has been conducted on "Automated Employment Decision Tools"; results are available for Ashby .
If you're applying for a role at and have questions about how we use AI in our process, or if you'd like to request information about the data we collect, please contact careers@.com .
We are committed to providing equal employment opportunities to qualified applicants and do not discriminate on the basis of race, color, ancestry, religion, sex, pregnancy, gender, gender identity, gender expression, sexual orientation, national origin, age, marital status, genetic information, disability, protected veteran status or any other characteristic protected by federal, state, or local laws.