Remote AI Tooling Engineer for Production Agents

Jobgether

Turkey

Remote

TRY 350,000 - 650,000

Full time

3 days ago

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Benefits offered by this job

Fully remote work

Multicultural team

Cutting-edge AI technology

End-to-end ownership of projects

Career growth opportunities

Job summary

Jobgether is seeking an AI Tooling Engineer based in Turkey to develop and scale an internal agentic platform unifying knowledge, data, and tools in a secure environment. You will build production-ready AI agents and integrations to empower employees and AI assistants, owning the full lifecycle from design to deployment and optimization.

You will use Python, LangGraph, LLM APIs, and MCP to transform prototypes into reliable tools used organization-wide.

Qualifications

At least 3 years building and shipping production software using Python and relational databases.
Proven experience deploying at least one production AI agent with LangGraph used by real users.
Practical expertise in agent development including tool calling, retrieval and embeddings, prompts, and context design.
Hands-on experience with LLM APIs from major providers, including token management and cost optimization.
Experience with MCP or comparable tool protocols, server and client.
Strong understanding of AI evaluation methodologies, test datasets, regression testing, and monitoring.
Familiarity with tracing and observability tools such as Langfuse or equivalents.
Experience integrating APIs and data sources including SaaS and SQL databases.
Cloud infrastructure experience on GCP/AWS, containers, managed DBs, IAM, and CI/CD.
Daily use of AI coding agents, with high code quality expectations.
Strong security principles, identity management, permissions, and least-privilege access.
Experience with GitHub or Bitbucket for collaboration.
Excellent written and spoken English for technical communication.

Responsibilities

Collaborate with Principal Engineer to design, develop, and deploy new platform capabilities.
Integrate internal systems and SaaS by connecting APIs, data models, and access perms.
Build AI agents and MCP servers enabling interactions with internal systems.
Design/optimize retrieval workflows, embeddings, prompts, and context management.
Establish AI quality standards with datasets, benchmarks, regression tests, tracing.
Monitor performance metrics like cost per answer and token usage; optimize.
Troubleshoot production issues and incorporate user feedback for improvements.
Turn PoCs into secure, scalable cloud apps with proper infrastructure and IAM.