Software Engineer - AI Tooling
New
J
JobgetherAI developer tools
Based in SloveniaFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- At least 5 years of professional software engineering experience.
- Required Skills
- PostgreSQLJavascriptTypeScript
Requirements
- At least 5 years of professional software engineering experience.
- Strong proficiency in TypeScript.
- Extensive knowledge of the JavaScript ecosystem, including npm, ES modules, bundlers, and compatibility considerations.
- Deep familiarity with AI tools, agent architectures, development patterns, and their practical trade-offs.
- Experience building developer tools, product interfaces, or platform components used by other engineers.
- Experience designing, implementing, or working with evaluation frameworks for AI quality, reliability, and task success.
- Understanding of evaluation baselines, performance variance, cost considerations, and measurable quality improvements.
- Solid testing practices and experience validating software reliability under real-world conditions.
- Good knowledge of PostgreSQL and relational database principles.
- Excellent written communication and ability to collaborate across engineering, product, and documentation teams.
- Experience with vector databases, embeddings, semantic search, pgvector, customer-facing AI features, or AI evaluation and tracing platforms is advantageous.
Responsibilities
- Design, develop, and improve AI-powered developer tools, including MCP servers, intelligent agents, agent skills, and dashboard assistants.
- Build tools, integrations, skills, and evaluation frameworks that make products accessible to AI agents.
- Prototype emerging AI technologies and assess which solutions are suitable for production.
- Develop evaluation frameworks, instrumentation, and feedback loops to measure AI tool quality and effectiveness.
- Benchmark tools against no-tool baselines, monitor performance, and define quality indicators and release criteria.
- Analyze developer and AI-agent interactions with existing tools and use insights to improve interfaces, documentation, and functionality.
- Structure and expose technical documentation and product knowledge for AI agents, measuring accessibility and effectiveness.
- Develop reusable tools and patterns for customer AI integrations, including MCP integrations with Edge Functions, vector embeddings, and agents running on Edge Functions.
- Provide contribution guidelines, templates, documentation, and review processes for teams contributing to AI capabilities.
- Collaborate with infrastructure and engineering teams on hosting, authentication, scalability, reliability, testing, and production readiness.
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