AI Tooling Engineer: Build Internal AI Agents (Remote)

Jobgether; Switzerland; Remote; CHF 140,000 - 200,000; Full time

Benefits offered by this job

Fully remote work

Multicultural team

Cutting-edge AI technologies

Shape AI tooling across organization

End-to-end ownership

Job summary

Jobgether is seeking an AI Tooling Engineer in Switzerland to build and scale an internal agent-based platform that unifies company knowledge, data, and tools with secure access. You will own the full lifecycle from design to deployment, partnering with a Principal Engineer to ship production-ready AI agents and integrations across the organization.

You will work with Python, LangGraph, LLM APIs, and MCP to optimize performance, costs, and security while enabling cross-team collaboration on

Qualifications

• At least 3 years of experience building and shipping production software, primarily using Python and relational databases.
• Proven experience building and deploying at least one production AI agent with LangGraph that is used by real users.
• Practical expertise in agent development, including tool calling, retrieval and embeddings, prompt engineering, and context design.
• Hands-on experience with LLM APIs from major providers, including token management and cost optimization.
• Experience working with MCP or comparable tool protocols, both as a server and as a client.
• Strong understanding of AI evaluation methodologies, including test datasets, LLM-as-judge approaches, regression testing, and performance monitoring.
• Familiarity with tracing and observability tools such as Langfuse or equivalent solutions.
• Experience integrating APIs and data sources, including SaaS applications, SQL databases, and data warehouses.
• Practical experience with cloud infrastructure on Google Cloud Platform (GCP), Amazon Web Services (AWS), or both, including containers, managed databases, identity and access management, and CI/CD pipelines.
• Daily use of AI coding agents, with the ability to validate their output and maintain high standards of software quality.
• Strong understanding of security principles, identity management, permissions, and least-privilege access controls.
• Experience with version control and collaborative development tools such as GitHub or Bitbucket.
• Excellent written and spoken English, with the ability to communicate technical concepts clearly to both technical and non-technical audiences.

Responsibilities

• You will help develop and maintain an internal AI platform, combining agent development, systems integration, production engineering, and continuous optimization to deliver practical tools that improve how teams work.
• Collaborate with the Principal Engineer to design, develop, and deploy new platform capabilities, taking ownership from initial design through production release.
• Integrate internal systems and SaaS applications by connecting APIs and data sources, defining shared data models, and implementing appropriate access permissions.
• Build AI agents and supporting tools, including MCP servers that enable agents across the organization to interact with internal systems and retrieve relevant context.
• Design and improve retrieval workflows, tool calling, embeddings, prompts, and context management to deliver accurate and useful AI-generated responses.
• Establish and maintain AI quality standards through evaluation datasets, benchmarks, regression testing, tracing, and observability.
• Monitor performance indicators, including cost per answer and token usage, and optimize models, prompts, and workflows for efficiency and reliability.
• Troubleshoot production issues, incorporate user feedback, and continuously improve the platform based on real-world usage.
• Turn proofs of concept into secure, scalable cloud applications with appropriate infrastructure, deployment processes, and identity and access controls.
• Use AI coding agents as a core part of the development workflow while maintaining code quality through clear specifications, automated tests, reviews, and sound engineering practices.
• Contribute to company-wide AI tooling initiatives, including evaluating and standardizing internal AI tools, tracking usage and costs, and defining standards for AI-generated applications.
• Support other teams in adopting and building on the platform, helping them develop effective AI-powered workflows and internal applications.
• Engage with technical and non-technical stakeholders across the organization to understand their needs, prioritize improvements, and communicate solutions clearly.

Skills

Python

AI agent development

LangGraph

LLM APIs

MCP protocol

Cloud platforms (GCP/AWS)

Security & IAM

Git

English

Relational databases

Tools

LangGraph

pgvector

Django

PostgreSQL

React

Next.js

GCP

AWS

Job description

Jobgether is seeking an AI Tooling Engineer in Switzerland to build and scale an internal agent-based platform that unifies company knowledge, data, and tools with secure access. You will own the full lifecycle from design to deployment, partnering with a Principal Engineer to ship production-ready AI agents and integrations across the organization.

You will work with Python, LangGraph, LLM APIs, and MCP to optimize performance, costs, and security while enabling cross-team collaboration on