AI Developer

Job Summary

The AI Developer at Gaia is responsible for creating scalable backend systems and integrating advanced AI functionalities into enterprise applications, focusing on production-ready AI-powered software rather than traditional machine learning research.

Responsibilities

• Design and maintain scalable backend services, APIs, and microservices.
• Develop and integrate applications powered by large language models (LLMs), AI assistants, and autonomous agents.
• Create agentic workflows including tool calling, function execution, planning, and orchestration.
• Implement retrieval-augmented generation (RAG) pipelines, semantic search, embeddings, reranking, and context retrieval.
• Integrate enterprise platforms and third-party services using MCPs, APIs, webhooks, and connectors.
• Build reliable asynchronous processing, background jobs, and event-driven workflows.
• Optimize AI application performance, latency, reliability, and inference costs.
• Implement security measures such as authentication, authorization, access controls, and secure data handling.
• Collaborate with AI, product, and infrastructure teams to deliver production-ready features.

Must haves

• Strong proficiency in Python and backend frameworks like FastAPI.
• Experience designing REST APIs, asynchronous services, and distributed systems.
• Knowledge of PostgreSQL, Redis/Valkey, and database optimization.
• Hands-on experience integrating LLMs via APIs or self-hosted inference.
• Understanding of RAG, embeddings, vector databases, and semantic search.
• Familiarity with agent frameworks, orchestration patterns, and LLM tool/function calling.
• Experience with Docker, Git, CI/CD pipelines, and cloud deployments.
• Strong software engineering fundamentals including testing, debugging, observability, and clean architecture.

Nice to haves

• Experience with vector databases, hybrid retrieval, and reranking pipelines.
• Familiarity with LangGraph, LangChain, LlamaIndex, or custom agent runtimes.
• Knowledge of Kubernetes, Terraform, and cloud platforms such as AWS, Azure, GCP, or OCI.
• Experience building multi-tenant SaaS applications and enterprise integrations.
• Understanding of AI evaluation, guardrails, prompt injection defense, and permission-aware retrieval.
• Experience with MCP and AI tool integrations.

We refresh listings regularly, but some roles close early on the source platform.