Senior Partner Deployed Engineer

3 нед. назад

120k–227k GBP / yearEuropeWorldwideSeniorRemote

kubernetes

Senior Partner Deployed Engineer at working on partner ecosystem across EMEA combining strategic, technical, and partner relations roles.

Обязанности

We are looking for a Senior Partner Deployed Engineer to join the Customer Solutions team, focused on building ’s partner ecosystem across EMEA. This is a new function at , modeled on the Forward Deployed Engineer role pioneered by companies like Palantir and now the fastest-growing technical role at frontier AI companies. The difference: instead of embedding with a single customer to deploy a platform, you embed with strategic partners to help them understand, position, and deliver ’s platform across their entire customer base.
You are part Field CTO, part Industry Strategist, part Technical Specialist, and part Partner Relations Lead. You will be the technical authority within our EMEA partner ecosystem: setting the vision for how fits into each partner’s AI, cloud, and modernization offerings, co-creating the GTM sales plays that partner sellers take to market, building the demonstrations and workshops that generate pipeline, and producing the Partner Relations content that establishes ’s technical brand in the ecosystem.
This is not a support role. You are equally comfortable holding a strategic roadmap conversation with a partner CTO and debugging a Kubernetes deployment in a partner’s lab in the same afternoon. You are energized by the challenge of building a new category through partnerships, motivated by the multiplied impact of enabling an entire ecosystem rather than a single customer, and capable of operating with full autonomy in a fast-moving startup environment.

Будет плюсом

(Bonus tacos? That’s how we say thanks at . Ask us about it.)
Prior Forward Deployed Engineer experience at a platform company (Palantir, Scale AI, frontier AI lab, or equivalent embedded deployment model)
Track record of public technical advocacy: blog posts, conference talks, open-source contributions, or developer/partner community engagement
Experience with hyperscaler partner programs (e.g., ISV Accelerate, strategic collaboration agreements, co-sell programs) at an operational level
Familiarity with European regulatory environments: GDPR, DORA, NIS2, AI Act compliance requirements, and data sovereignty patterns for cloud-native deployments
Experience with air-gapped or network-isolated deployments common in European financial services, government, or defense contexts
Background in AI governance frameworks, session audit requirements, or SIEM integration for AI workloads
Experience with LLM gateway or proxy infrastructure (LiteLLM, OpenRouter, or equivalent) in a multi-team or enterprise context
Experience designing human-in-the-loop breakpoints or escalation patterns for autonomous agent workflows
Kubernetes certification (CKA, CKAD, or CKS)
Experience with Tailscale or similar overlay networking tools
Open-source contributions, particularly in CNCF, MCP, or AI agent ecosystems
Existing relationships with hyperscaler EMEA solutions architecture teams, European GSI technical practices, or AI infrastructure partner ecosystems
Fluency in German, French, or a Nordic language in addition to English

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

Serve as the strategic technical thought partner to EMEA partner leadership, including practice leads, CTOs, and solutions architects at global systems integrators, regional cloud consultancies, and hyperscaler field teams. Own the technical relationship and set the vision for how fits into each partner’s AI and modernization portfolio.
Co-create sales plays tailored to each partner’s customer base, vertical focus, and services capabilities. Author Working Backwards outcome proposals for strategic partner-customer combinations that translate AI Development Infrastructure into deal-level urgency.
Develop and deliver workshops, Builder Labs, and partner-hosted enablement sessions as the primary awareness and demand generation vehicle for the EMEA ecosystem. Build hands-on demonstration environments and interactive experiences that partners can use independently.
Intervene directly on the highest-value partner-attached deals across EMEA: co-sell calls, technical discovery, PoV scoping, architecture review, and technical win support. Own the engagement until the partner’s team can carry it independently.
Transform bespoke partner enablement sessions into structured LMS modules and certification tiers that scale across the EMEA partner base without requiring live PDE support for each new partner.
Produce “better together” reference architectures for strategic partner combinations across cloud providers and AI platforms. Include deployment diagrams, network topology, IAM patterns, and operational runbooks that partner SAs can hand directly to customers.
Codify each successful partner engagement into a repeatable GTM play: trigger conditions, discovery questions, positioning framework, demo script, PoV scope template, and expected outcomes. Build a playbook library that a new PDE or partner seller can pick up and run.
Build AI-powered self-service tools that automate high-volume PDE activities: Opportunity Brief Generator, PR/FAQ Generator, Workshop-in-a-Box deployment, and demo site builder.
Produce a monthly partner intelligence digest from EMEA engagements: what customers are asking for, how competitors are positioning, where integrations are missing, which vertical use cases are emerging. Distribute to Product, Engineering, and GTM leadership.
Own the EMEA-relevant portions of the joint technical integration roadmap with strategic partners. Define priorities cross-functionally with Product and Engineering based on field signals from the EMEA market.
Create and publish Partner Relations content, the ecosystem equivalent of Developer Relations: technical blog posts, cookbooks, partner ecosystem conference talks, enablement videos, and workshop recaps. Build ’s technical brand within the EMEA partner community.
Contribute to cloud marketplace product listing stewardship, competency maintenance documentation, and CSP co-build technical requirements as they apply to EMEA-specific partner and compliance contexts.
7+ years of experience in a combination of Forward Deployed Engineering, Solutions Architecture, Field CTO, Technical Consulting, or Developer Relations roles at an infrastructure, developer tools, or AI company
Demonstrated experience helping partners or customers understand and adopt products in emerging or undefined categories, not just executing playbooks for established ones
Proven hands-on experience designing and deploying cloud infrastructure on at least one major cloud provider (AWS, Google Cloud, or Microsoft Azure), with production-level Kubernetes and Terraform depth. You have done the work and can speak to it with specificity.
2+ years deploying or operating AI coding agents in a production or near-production environment: you understand how agent loops execute, where credentials live, and what governance and audit requirements look like in a European enterprise context
Ability to articulate the architectural difference between workspace-local agent tooling and a centralized agentic harness, and to explain why that distinction matters to a security, compliance, or data sovereignty stakeholder
Experience working with channel or technology partners in a co-sell model: hyperscaler partner programs, GSI/RSI partnerships, or VAR/distributor ecosystems in EMEA markets
Experience building repeatable technical GTM assets that scaled beyond your personal delivery: sales plays, enablement curricula, reference architectures, or technical content programs
Executive communication and Field CTO credibility: you can hold a technical vision conversation with a partner CTO and a deal-level architecture review with an SE in the same day, in English and ideally at least one additional European language
Strong written communication: you can produce a Working Backwards PR/FAQ, a technical architecture document, and a blog post without those being separate skills requiring separate people
Self-directed, analytically minded, and comfortable operating with full autonomy. You will define processes that don’t exist, build tools that haven’t been scoped, and create a function from first principles in a new region.
You have done the hard technical work before: deploying cloud-native infrastructure, navigating Kubernetes in production, building with Terraform, and operating in the complexity of large European enterprise environments. You bring that credibility into every partner conversation.
You can walk a partner CTO through how enables parallelized AI agents in a regulated European enterprise, covering credential isolation, audit lineage, GDPR-compliant data handling, and escalation design, and turn that conversation into a joint GTM play their sellers can run next quarter.
You can walk into an unstructured partner relationship, assess the technical and commercial opportunity, and chart a path from first enablement session to first co-sourced deal without waiting to be told what to do.
You translate deep technical knowledge into assets that scale: reference architectures partners hand to their customers, enablement modules partners consume on their own, and GTM playbooks partner sellers run without PDE involvement.
You are as invested in the pattern behind the engagement as you are in the engagement itself. Every bespoke partner interaction produces a reusable artifact. Every field insight feeds back to product. You codify by instinct.
You make the ecosystem and the product better: your field experience shapes how builds integrations, how partners deliver, and how the EMEA market understands AI Development Infrastructure as a category.
Location: Remote EMEA (UK preferred)
Department: Customer Solutions
Reports to: Sr Manager, Solutions Engineering
is an AI software development company leading the future of autonomous coding. We empower teams to build software faster, more securely, and at scale through the collaboration of AI coding agents and human developers. Our mission is to make agentic AI a safe, trusted, and integral part of every software development lifecycle.
Our self-hosted AI Development Environment is the foundation for deploying agentic AI in the enterprise. It provides a secure, standardized, and governed workspace to deploy autonomous coding agents alongside human developers, accelerating innovation while maintaining control and compliance. 's isolated, policy-driven environments improve productivity, cut cloud costs, and reduce data risks. Developers transition to AI at their own pace using their own tools. Platform and security teams can govern, audit, and manage a great developer experience at scale.
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.
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