CAREERS

Build AI products that work in production.

At TameTeq, we combine AI speed with senior engineering discipline. We deliver AI systems, automation, backend APIs, and web applications that are reliable, measurable, and built to scale.

Open Positions

We are looking for engineers who take ownership from architecture to deployment, move fast with intent, and care about real business results.

AI Systems Engineer

Mid-Senior / Senior

Design and deliver production AI systems end-to-end, from agents and RAG pipelines to AI-supported automation integrated into real product workflows.

Core Requirements

  • Strong foundations in Python and backend engineering
  • Hands-on experience with LLM applications, agent orchestration, and tool/API integration
  • Practical knowledge of RAG: ingestion, retrieval, evaluation, and quality iteration
  • Experience integrating AI systems into existing products and internal tools
  • Production mindset: reliability, traceability, security, and cost awareness
  • Comfortable with ambiguity, rapid iteration, and end-to-end responsibility

Nice-to-haves

  • MCP and tool ecosystems for agents
  • Fine-tuning custom models or domain-specific ML pipelines
  • Experience with planning and optimization (scheduling, routing, resource allocation)
  • Vector databases and evaluation frameworks

Full Stack Product Engineer

Mid-Senior / Senior

Build and develop production-ready products end-to-end, from backend APIs and integrations to fast web experiences and AI-powered features.

Core Requirements

  • Strong TypeScript and solid experience with modern web stacks (Next.js/React)
  • Strong backend foundations: API design, integration, data modeling, and authentication
  • Experience delivering maintainable production web applications
  • Focus on performance, reliability, security, and clean engineering practices
  • Experience with DevOps (CI/CD, Docker, deployment workflows)
  • Ability to work across the product lifecycle: discovery, MVP, and iterative delivery

Nice-to-haves

  • Integration of AI features into product UX
  • SEO, accessibility (a11y), and frontend performance optimization
  • Refactoring and modernizing legacy systems
  • Monitoring, logging, and traceability in production