[Hiring] Head of Engineering @Valis

Role Description

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.

Qualifications

• 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.

Benefits

• Competitive base salary.
• Performance-based bonus.
• Opportunity to join the team during fast growth.