WorkMotionHiring

AI Engineer (Agentic Systems & LLM Services)

  • Remote, Europe
  • Full-time
  • Mid-level
  • Posted 10 days ago
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In one line

Full-time remote AI engineering job on a worldwide team, with hours kept within two hours of CET.

About the role

Remote setup with a distributed crew. Work centres on taking agent and LLM services from early prototypes through to running systems that stay measurable and secure.

At a glance

Pay
Not stated in the posting
Remote scope
Remote, Europe
Seniority
Mid-level
Employment
Full-time
Working hours
Within +/- 2 hours of CET
Skills
Python, Pydantic, SQLAlchemy, Docker, AWS, MCP, RAG
Posted
19 Oct 2026
Last checked
29 Oct 2026

What you will do

  • Create and maintain MCP servers and integrations giving agents scoped access to company systems.
  • Improve quality through benchmarks, regression tests, replays of real cases and prompt iteration, watching cost and latency.
  • Operate deployments with containers, observability and authentication, and handle employee and customer data safely.

What they look for

  • At least three years of software engineering, backend or Python, with one year or more of LLM applications in production.
  • Hands-on LLM tooling: agent frameworks like Google ADK, LiteLLM or similar gateways, function calling, MCP, RAG with vector databases.
  • Docker, AWS including S3, CI/CD and observability tooling.
  • Fluent English, pragmatic problem solving, clear writing, ownership and sound data privacy judgment.

Nice to have

  • Salesforce or Atlassian APIs, or HR, payroll and global employment data.
  • Python, Node.js or TypeScript experience, since some MCP tooling uses them.
  • Past work building evaluation uses or benchmarks for LLM systems.

Benefits

  • Full-time contract with a yearly salary starting at 45,000 EUR gross, set by location, skills and experience.

How Keywordise applies for you

  1. 1Upload your CVAdd your CV once. It takes about a minute.
  2. 2Tailored to this jobKeywordise writes a CV and a cover letter for this job from your real experience.
  3. 3The form fills itselfName, email, experience and screening questions, field by field.
  4. 4Application sentYou get a receipt and follow it in your dashboard.

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ClaudeConnectorChatGPTConnectorMuseby Meta

Claude

  1. In Claude, open Settings, then Connectors, and choose Add custom connector.
  2. Name it Keywordise and paste the connector URL.
  3. Click Connect, log in to Keywordise and approve. Then send the prompt in a new chat.
Connector URL
https://keywordise.com/mcp

Disconnect any time in your Keywordise settings.

ChatGPT

  1. In ChatGPT, open Settings, then Connectors. On plans that need it, turn on developer mode first.
  2. Add a new connector with the connector URL and choose OAuth. Leave the client ID and secret empty.
  3. Log in to Keywordise and approve. Then send the prompt in a new chat.
Connector URL
https://keywordise.com/mcp

Disconnect any time in your Keywordise settings.

Muse

  1. Open Muse (muse.ai or the app) and send it the message below.
  2. If Muse asks how to sign in, answer OAuth. Open the sign-in link it sends, log in to Keywordise and approve.
  3. Send the prompt. Muse asks before it sends anything.
Message for Muse
Add a custom connector called Keywordise. It is a remote MCP server at https://keywordise.com/mcp and uses OAuth. Give me the sign-in link.

Muse is available in the US only for now.

Prompt
Apply to Keywordise job 4f3dgvdak6
How to connect

Questions about this job

Is this a remote job, and where can I work from?

Yes, it is listed as remote, aimed at candidates in Europe. On hours, the posting says: Within +/- 2 hours of CET.

What does this job pay?

The posting does not state a salary, so there is no figure to quote.

What experience is needed?

It is a mid-level role. The posting asks for: at least three years of software engineering, backend or Python, with one year or more of LLM applications in production; hands-on LLM tooling: agent frameworks like Google ADK, LiteLLM or similar gateways, function calling, MCP, RAG with vector databases; docker, AWS including S3, CI/CD and observability tooling. Skills it names include Python, Pydantic, SQLAlchemy, Docker.

How do I apply with Keywordise AI?

Press the Apply with Keywordise AI button and add your CV. Keywordise tailors your CV and cover letter to this posting and sends the application for you, with a free 7-day trial and no card.

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