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Salary
≈ $39k – $97k per year (Estimated)
Location
Hybrid (Lisbon, Portugal)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Apr 27, 2026. Thorit scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Thorit is a German CRM and HubSpot consultancy that helps companies grow digitally with customer experience strategies and IT solutions. It designs architectures spanning CRM, data, integrations, custom software and agentic AI for corporate clients and hires solution architects, business consultants, project managers and agentic engineers in Böblingen and Lisbon. The company is headquartered in Böblingen, Germany.

About the Role

You'll design and ship production multi-agent systems for enterprise clients, the AUTOMATE layer of our Agentic Growth Stack. That means orchestrating fleets of LLM agents that qualify leads, draft outreach, coach revenue teams, and write back to CRM, on a reliability bar where they actually run in production for months without losing the plot.

You'll own the orchestration topology, the tool ecosystem, the agent memory architecture, the human-in-the-loop checkpoints, and the observability stack.

This is engineering, not research. We ship.

What You'll Do

  • You'll ship 3+ production multi-agent systems to enterprise clients within your first 12 months (deployed, signed-off, in active use as AUTOMATE-layer engagements)

  • You'll build and maintain our reusable agent orchestration framework: orchestrator pattern, tool-calling layer, agent memory layer, human-in-the-loop hooks, observability hooks, usable by every future Agentic Engineer across all sites

  • You'll establish our agent observability and reliability stack: tracing, cost dashboards, drift monitoring, error-recovery and fallback patterns, with documented SLAs per agent type

  • You'll establish our agent quality bar: every shipped multi-agent system has documented orchestration-level evals (not just per-tool unit evals), a rollback plan, and an incident playbook

  • You'll co-author 2+ public-facing technical assets (blog post, webinar, conference talk) on our multi-agent architecture approach

  • You'll contribute as the agent architect in pre-sales scoping alongside Sales, Advisory, and the Head of AI when in seat

What You Bring

Must-haves

  • Production experience shipping multi-agent systems beyond prototypes (orchestrator-plus-sub-agents, supervisor patterns, agent-to-agent handoffs). You can walk us through what you shipped, what broke, and how you fixed it

  • Hands-on production experience with at least one major agent framework (LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, Pydantic AI, Mastra, or comparable), and a credible point of view on why one over another for a given engagement

  • Track record of long-running agent loops (10+ steps) holding up in production: state management, retry policies, max-step caps, looping detection, graceful recovery from tool failure

  • Production fluency with agent observability and tracing (LangSmith, Helicone, Arize, Langfuse, or self-built). You read traces like an SRE reads CPU

  • Tool design instinct: you've tuned tool schemas and docstrings based on observed model behaviour, and you know when a tool should be one tool vs. several vs. a sub-agent

  • Strong Python or TypeScript with tests, types, CI, deployment in cloud (AWS, GCP, or Azure), Docker, and basic IaC

  • Native-level Portuguese plus business-fluent English

Nice-to-haves

  • Public open-source contributions to agent frameworks (LangGraph, LangChain, CrewAI, etc.)

  • Shipped commercial multi-agent products at scale (B2B SaaS, agentic platforms, enterprise AI products)

  • Direct HubSpot or comparable CRM integration experience

  • Eval engineering background at the orchestration level (not just unit-level model evals)

Your Team

You'll report directly to the Director Development & Technology, with a dotted line to the Head of AI & Agentic Delivery once that role is in seat. You'll join the AI Team as the Lisbon anchor for agent orchestration. Day-to-day, you'll work closely with the AI & Data Engineer (single-agent and data foundation), the Director D&T (technical sign-off and architecture review), and the broader Lisbon hub.

Tech Stack

  • Languages: Python and TypeScript

  • Agent frameworks: LangGraph, LangChain, AutoGen, CrewAI, Pydantic AI, Mastra (we pick per engagement)

  • LLMs: Anthropic Claude (we are an Anthropic Build Partner), OpenAI, Gemini, with self-hosted options where the engagement demands it

  • Observability: LangSmith, Helicone, Langfuse, Arize

  • Cloud and DevOps: AWS, GCP, Azure, Docker, GitHub Actions, basic IaC

  • CRM and integration: HubSpot APIs (REST, GraphQL, webhooks)

  • Collaboration: Jira, Confluence, Forecast, Claude AI, Claude Code, Cursor

What We Offer

  • Statutory: Standard Portuguese employment benefits via local entity or EOR (paid time off, public holidays, parental leave, statutory health coverage)

  • Health: Private health insurance top-up

  • Learning: Full Blinkist Business library (4,500+ books), 3 months of Babbel, dedicated AI conference and training budget

  • Flexibility: Up to 4 weeks per year working from anywhere in the EU with a €500 allowance, hybrid setup with Lisbon hub access

  • Culture & Tools: Flat hierarchies with direct access to CEO and Leadership, modern stack (HubSpot, Jira, Confluence, Claude AI), Anthropic Build Partner status with early access to Claude capabilities

About Thorit

Thorit is one of Europe's leading HubSpot partners and a top business and technology consultancy. We combine strategic advisory with hands-on IT implementation, from CRM architecture to fully automated go-to-market infrastructure powered by AI and agentic systems.

Ready to Apply?

Send your application via Ashby. A cover letter is optional, but a concrete example of a multi-agent system you have personally shipped to production (architecture, framework choice, what broke and how you fixed it) is required. Public links (GitHub, blog post, demo video) appreciated.

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