# Agentic Engineer (all genders) at Thorit > Portugal · Unspecified · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3Athorit%3A13fc5ea3-8d7e-4be1-b41b-437aec00d4a1 (read 2026-11-04). ## Facts (observed) - Company: [Thorit](https://alderhq.app/companies/thorit) - Location text: Lisbon Office - Where it can be done from (inferred): Portugal (evidence: "Location: Lisbon Office") - Posted: 2026-04-27 (190 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-03 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/thorit/13fc5ea3-8d7e-4be1-b41b-437aec00d4a1 - Skills listed (inferred): TypeScript, Python, GraphQL, AWS, GCP, Azure, Docker, LLMs ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (Lisbon, n 6): p25 €49k, median €57k, p75 €62k ## Description (the employer's text) ### 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 --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Athorit%3A13fc5ea3-8d7e-4be1-b41b-437aec00d4a1 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.