Senior Polyglot Engineer
Job Type
Full Time
Experience
5+ years
Location
US
Job Description
We are looking for a versatile Senior Polyglot Engineer to lead the development of our next-generation AI-powered platforms. This is not a standard full-stack role; you will be responsible for architecting retrieval-augmented generation (RAG) systems, optimizing LLM workflows, and building seamless user interfaces that make complex AI interactions intuitive. You should be as comfortable tuning a MongoDB aggregation pipeline as you are designing a React component or optimizing an embedding search.
Key Responsibilities
End-to-End AI Engineering: Design and deploy production-grade RAG pipelines and Agentic workflows using frameworks like LangChain or LlamaIndex.
Backend Excellence: Build high-performance, asynchronous microservices using Python and FastAPI, ensuring secure and scalable API design.
Frontend Sophistication: Develop responsive, state-driven interfaces in React to handle complex AI outputs (streaming responses, citations, and interactive data).
Data Architecture: Manage and optimize data flows across MongoDB (NoSQL) and Vector Databases (e.g., Pinecone, Milvus, or Weaviate) for semantic search.
Cloud Infrastructure: Architect and maintain scalable AI services on AWS, leveraging services like Lambda, SageMaker, Bedrock, and ECS/EKS.
AI Observability: Implement monitoring for LLM performance, including latency, token usage, cost optimization, and hallucination detection.
Qualifications
1. AI & Machine Learning
Deep understanding of LLMs (OpenAI, Anthropic, Llama 3) and prompt engineering.
Hands-on experience with RAG (Retrieval-Augmented Generation) and vector embeddings.
Experience with AI orchestration (LangChain, LangGraph, or CrewAI).
2. Backend & Data
Expertise in Python (AsyncIO, Type Hinting, Pydantic).
High proficiency in FastAPI for building RESTful and WebSocket-based services.
Strong experience with MongoDB (Schema design, indexing, and aggregation).
3. Frontend
Strong command of React.js and modern state management (Zustand, Redux, or React Query).
Experience building interfaces for real-time data streaming and AI-driven UX.
4. Cloud & DevOps
Proficiency in AWS ecosystem (S3, EC2, IAM, and AI-specific services).
Experience with Docker and CI/CD pipelines for automated testing and deployment.