Head of Engineering

Valis; Netherlands; On-site; EUR 150,000 - 210,000; Full time

Benefits offered by this job

Competitive base salary

Performance-based bonus

Fast growth opportunities

Job summary

Valis seeks a CTO-level engineering leader to own platform architecture for a next-gen AI operating layer, from data ingestion to agent orchestration. You will personally code where it matters and shape multi-tenant, GDPR-compliant systems with strong security and cost control.

You will lead the buildout of MCP servers and connectors to Slack, Google Workspace, Asana, HRIS, DWH and ERP, delivering self-service deployments at scale. Fluent English required for executive client interactions.

Qualifications

• Must have 10+ years in software engineering with leadership at CTO/VP level.
• Hands-on engineering with production-grade systems.
• Deep experience running LLMs in production: agents, RAG, tool use and MCP.
• Strong backend architecture and data engineering capabilities.
• Experience hiring and managing an engineering team.

Responsibilities

• Own platform architecture including data ingestion, storage, retrieval, agents and integrations with LLMs.
• Code hands-on where it matters and contribute technically beyond management.
• Design access control, data retention, GDPR compliance and multi-tenancy.
• Build MCP servers and connectors to client systems for self-service deployment.
• Lead complex technical discussions and own deployments.
• Turn client-specific work into repeatable products and serve as escalation point.

Skills

CTO leadership

Backend architecture

LLMs in production

Cost control

Client communication

Team building

Cloud infra

Data engineering

MCP tools

Tools

AWS

GCP

Redshift

DuckDB

CI/CD

Slack

Job description

About us

We are Valis - a company building an institutional AI operating layer for mid-market companies: shared company memory, workflow mining and agentic automation.

Why this role exists

We are hiring a CTO-level engineering leader. We need a strong person, able to own a major part of the technology from architecture through production, build their own team, and speak with clients at C-suite level.

What you will do

• Platform architecture and engineering - Own the architecture of the org brain and personal brain: data ingestion, knowledge storage, retrieval, agents, and integrations with Claude and other LLMs.
• Write code yourself where it matters most. This is a hands-on role, not only a management one.
• Design access control so each user sees only data from their own area. You will also own data retention and deletion, GDPR compliance, and multi-tenancy.
• Build MCP servers and connectors to company systems (Slack, Google Workspace, Asana, HRIS, DWH, ERP), and bring them to the point where clients can use them self-service.

Deployments

• Lead complex technical conversations
• Own the technical side of deployments
• Turn what works for one client into a product, so the same custom work is not repeated.
• Be the final technical escalation point for your area.

Infrastructure, data and cost

• Cloud infrastructure (AWS/GCP, Cloudflare), CI/CD, observability and security.
• The data stack: data warehouse (Redshift, MotherDuck/DuckDB), ETL, and large-scale migrations.
• Platform costs: token and inference spend, subscriptions, and vendor negotiations.

Team

• Hire people, develop them, and let them go when needed. Hire people stronger than yourself.
• Build an engineering culture where the team owns outcomes and needs little day-to-day management.
• Use AI agents such as Claude Code as your main working tool, and make them the team's main tool too, not an experiment.

Must have

• 10+ years in software engineering, including 4+ years as CTO, VP Engineering, Head of Engineering, or Principal/Staff Engineer at a product company or a strong startup.
• A track record of building systems from zero to production with real users and real load. You must have built them yourself, not only led the teams that did.
• Deep hands-on experience running LLMs in production: agents, RAG, tool use and MCP, evals, and cost control. We are looking for real deployments, not pilots.
• Strong backend architecture and data engineering: distributed systems, integrations, data stores, security and access control.
• Experience managing an engineering team, including hiring and firing.
• The ability to explain a technical decision to a client's non-technical executives and win their support for it.
• Fluent English.

Nice to have

• Good working knowledge of RU language
• Experience in B2B SaaS, enterprise deployments, or forward-deployed engineering
• Experience with company data: HRIS, ERP, finance, organisational structure.
• A strong personal AI productivity setup.

We offer competitive base, performance-based bonus, and the opportunity to join the team during fast growth.