AI Backend Engineer - Hybrid CDMX
AI Backend Engineer - Hybrid CDMX
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$ 100000 - 110000
1 Vacancy
Job Description
Our client is looking for a Principal Backend Engineer to design and build the backend and GraphQL API architecture for AIpowered retrieval systems (RAG) and AI agent orchestration. Youll develop highperformance GraphQL APIs that serve LLMdriven search vector retrieval and graphbased recommendations to users in real time. Youll also develop frameworks and orchestration to coordinate autonomous AI agents at scale.
This role requires expertise in those areas to help architect and implement the right solutions for AIdriven retrieval. Youll work closely with the Head of Engineering to design scalable AIpowered APIs and retrieval pipelines while remaining handson with coding.
Tech Stack: Golang (preferred) Python GraphQL PostgreSQL Redis Kubernetes Azure Vector Databases (Weaviate Pinecone FAISS) Graph Databases (Neo4j AWS Neptune TigerGraph) AI Agent frameworks (LangGraph AutoGen CrewAI etc)
Why This Role
- Architect Code Youll actively design GraphQL APIs for AI retrieval and an AI agent platform while writing productiongrade code daily.
- AIPowered Search & Retrieval (RAG) Leverage your experience with vector search and knowledge graphs to define future system architecture.
- Scalability & Performance Ensure lowlatency highscale orchestration and retrieval in a GraphQLfirst environment.
Responsibilities
- Design build and optimize GraphQL APIs to serve AIpowered search and retrieval systems.
- Design build and optimize AI agent platform and framework to orchestrate autonomous agents.
- Handson coding 70 focusing on Golang & Python API development.
- Architect GraphQL queries mutations and resolvers to support LLMpowered recommendations.
- Optimize GraphQL query performance (batching pagination caching Dataloader optimizations).
- Guide and implement vector search and knowledge graph capabilities (Weaviate Pinecone FAISS Neo4j AWS Neptune TigerGraph).
- Expose RAG and GraphRAG retrieval systems through GraphQL API endpoints.
- Database design for customerfacing access patterns.
- Ensure GraphQL schema design is flexible scalable and AIfriendly.
- Implement security best practices (OAuth JWT rolebased access in GraphQL).
- Collaborate with ML/AI engineers to expose LLM models embeddings and knowledge graphs via APIs.
- Deploy and scale services in Azure (Kubernetes Terraform AKS).
What Were Looking For
- 5 years of backend development experience with strong Golang (preferred) and Python skills.
- Proven experience designing and optimizing GraphQL APIs for highperformance applications.
- Strong understanding of AI retrieval systems including RAG GraphRAG vector search and knowledge graphs (even if not currently in use).
- Exposure to AI agent frameworks and design patterns.
- Deep expertise in distributed systems microservices and GraphQL performance tuning.
- Experience integrating AIdriven APIs with GraphQL queries and resolvers.
- Azure cloud experience (AKS Functions Blob Storage CosmosDB).
- Proven track record of handson coding while also defining backend architecture and best practices.
Bonus Points
- Experience with GraphQL federation schema stitching or Apollo Gateway.
- Familiarity with GraphQL WebSockets (subscriptions for realtime AI updates).
- Exposure to MLOps and modelserving platforms (AWS SageMaker/Bedrock ClearML Triton).
Employment Type
Full Time
