Full-Stack AI Engineer â LLM Agents, MCP Servers & Applications
Full-Stack AI Engineer â LLM Agents, MCP Servers & Applications
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Job Description
About the Role:
We are hiring a Full-Stack AI Engineer to design and build intelligent software agents using Large Language Models (LLMs). This is a high-impact full-stack engineering role where youll build production-grade agentic applications across our core stack FastAPI (Python) (TypeScript) and GCP (Google Cloud Platform) with Cursor as your primary development environment.
Youll be a key contributor in implementing MCP (Model Context Protocol) servers which play a critical role in enabling rich context management and structured interaction between agents and models. Your work will span both backend infrastructure and frontend interfaces powering scalable context-aware AI systems.
Key Responsibilities:
- Design and build LLM-powered agent systems including planning tool use memory and user interaction flows.
- Implement and maintain MCP-compliant servers to facilitate structured contextual communication between agents and models.
- Develop FastAPI-based APIs to orchestrate and serve intelligent agent workflows.
- Build dynamic performant UIs in for interacting with agents and MCP-based systems.
- Use Cursor as your daily development environment for coding collaboration and debugging.
- Deploy and scale services on GCP including Cloud Run GKE and Vertex AI.
- Implement robust multi-agent orchestration patterns using frameworks such as AutoGen CrewAI or LangGraph enabling agents to collaborate delegate and reason over tasks in a coordinated manner.
- Integrate and manage vector databases especially Qdrant to provide long-term memory context retrieval and semantic search for LLM workflows.
- Collaborate closely with product and infrastructure teams to launch intelligent user-facing tools.
Requirements:
- 37 years of full-stack software development experience.
- Strong experience with Python FastAPI and TypeScript .
- Hands-on experience building and deploying LLM applications using APIs or open-source models (OpenAI Hugging Face etc.).
- Familiarity with MCP concepts such as structured prompts shared model state and protocol-driven interaction patterns.
- Experience designing or integrating MCP servers to support modular context-rich LLM workflows.
- Practical knowledge of vector databases like Qdrant including schema design and retrieval pipelines.
- Familiarity with orchestration frameworks (AutoGen CrewAI LangGraph) and multi-agent patterns (e.g. agent hierarchies shared context).
- Experience deploying and managing services on GCP infrastructure including CI/CD.
- Proficiency with Cursor as a development tool or a strong willingness to adopt it fully.
Nice to Have:
- Experience with agent tool integration (e.g. search APIs code execution environments).
- Understanding of prompt engineering chaining and dynamic task decomposition.
- Knowledge of LLM evaluation techniques including test harnesses and human-in-the-loop review.
- Exposure to observability and debugging in distributed agent environments.
- Contributions to open-source agent or protocol-based systems including MCP-compatible tools.
What Youll Gain:
- A chance to build some of the most advanced context-aware AI-powered agents in production.
- Full-stack ownership of intelligent systems that leverage the Model Context Protocol to improve reasoning traceability and modularity.
- A modern fast-paced development experience using Cursor backed by a collaborative and technically curious team.
- A front-row seat in shaping the next generation of LLM infrastructure and applications.
Required Experience:
Unclear Seniority
Employment Type
Full-Time
