Sr. AI Engineer (AWS | Node.js | Data Engineering | Pinecone Agentic Workflows)

Sr. AI Engineer (AWS | Node.js | Data Engineering | Pinecone Agentic Workflows)

Job Summary

AI Engineer

You will work across architecture, backend engineering, and AI workflow design—collaborating closely with data, frontend, and product teams in a Scrum environment.

Key Responsibilities

AI & Agentic Workflows

• Design and implement AI-powered workflows using Pinecone, LangChain/LangGraph, and custom orchestration tools
• Build RAG pipelines for semantic search, personalization, and LLM context enrichment
• Collaborate with AI teams to integrate GenAI features into production systems

Backend & Cloud Engineering

• Develop and maintain backend systems using Node.js (JavaScript/TypeScript)
• Architect scalable, secure solutions using AWS (Lambda, API Gateway, Cognito, RDS, DynamoDB, S3, IAM, VPC)
• Build and optimize relational/NoSQL databases (PostgreSQL, DynamoDB, Redis)

Data Engineering & Analytics

• Create and maintain ETL/ELT pipelines for structured/unstructured data
• Perform data cleansing, transformation, and indexing for performance optimization
• Enable analytics and insights through data modeling and querying

Collaboration & Agile Delivery

• Work in a Scrum team—participating in stand-ups, sprint planning, and code reviews
• Partner with frontend and AI teams to deliver features on time
• Maintain technical documentation and contribute to testing processes

Tech Stack

• Backend:

  Node.js, Python (for AI integration & data processing)

• AI Tools:

  Pinecone, LangChain, LangGraph, OpenAI APIs

• Cloud & DevOps:

  AWS services, Docker, Git, CI/CD pipelines

• Data Engineering:

  SQL, Python (Pandas, NumPy), ETL tools

• Databases:

  PostgreSQL, DynamoDB, Redis

• Frontend (optional):

  React, Next.js

Required Qualifications

• 6+ years as a backend/full stack engineer (Node.js focus)
• 3+ years in AWS architecture for production systems
• Strong experience with Pinecone/vector databases and AI agent orchestration
• Proven data engineering experience (pipelines, modeling, analytics)
• Solid understanding of RAG, LangChain/LangGraph, and agentic AI architectures
• Excellent collaboration and communication skills

Preferred Skills

• Experience with embedding models, HuggingFace, or LLM fine-tuning
• Familiarity with React/Next.js for end-to-end integration
• Knowledge of compliance frameworks (GDPR, HIPAA, SOC 2)