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Build and operate the cloud and MLOps infrastructure that powers Ingersoll Rand’s GenAI program, focusing on GCP, Snowflake, CI/CD, and AI observability.
Build and tune LLM-based AI agents and RAG systems for ERP automation and SaaS knowledge bases, using Python, PyTorch, LangChain, and cloud pipelines.
Build LLM-based agents and RAG systems for autonomous network operations, integrating fault diagnosis, predictive analytics, and closed-loop decision support using Python, LangChain, and vector/graph databases.
Build and deploy enterprise Generative AI apps using LLMs, RAG pipelines, and AI agents with Python, LangChain, and vector databases.
Build and maintain Python-based AI applications, embed AI capabilities into systems, and deploy on AWS for clients.
Build and maintain AI agentic backend systems using Python, LangChain/LangGraph, and vector databases to power autonomous workflows and RAG pipelines for business intelligence.
Builds and deploys LLM-powered features (agents, RAG, tools) with React/TypeScript frontends and Python or Go backends, integrating vector stores and agent frameworks.
Senior Full Stack Engineer building AI-driven applications with LLMs, LangChain/LangGraph, React, and Python; designs scalable systems integrating models, APIs, and modern UX.
Lead full-stack development using Node.js and React, design scalable systems with PostgreSQL/MySQL, and leverage MongoDB/Weaviate for data needs.
Build and optimize high-performance backends in Node.js, integrate APIs and distributed systems, and occasionally contribute to React frontends using PostgreSQL, MySQL, MongoDB, and Weaviate.
Builds and maintains the backend services and AI pipelines for an enterprise-grade conversational AI agent using Python, FastAPI/Flask, LangChain, and Google Gemini Enterprise on GCP.
Build AI-powered retail automation in Clojure: outfit generators, vector search, and LLM workflows that serve 100M+ shoppers via APIs for fashion retailers.
Build and deploy generative-AI backends in Python, designing RAG pipelines, AI agents, and scalable cloud infrastructure on GCP while owning CI/CD, Docker/Kubernetes, and IaC.
Build and maintain Python-based AI applications, integrating modern AI capabilities into systems using AWS and AI-powered tools like Claude Code.
Build and optimize backend services that ingest, index, and serve complex financial data for AI-powered workflows using PostgreSQL, ClickHouse, Kafka, and ElasticSearch.
Designs and builds secure, scalable backend services and REST/GraphQL APIs in Java/Spring Boot, and integrates agentic AI workflows using LLM frameworks for automation and decision support.
Design and build secure, scalable backend services and REST/GraphQL APIs in Java/Spring Boot, and integrate agentic AI workflows using LLM frameworks for automation and decision support.
Build and scale Python backend services for generative AI agents using LangChain/LangGraph, integrating LLMs and vector databases to power insurance and digital customer-service applications.
Principal Data Engineer builds and leads the AI data stack for Anaplan’s LLM and agentic systems, designing retrieval layers, vector/graph databases, and real-time GenAI features for enterprise planning workflows.
Principal Data Engineer builds and leads AI systems at Anaplan, designing retrieval layers, RAG pipelines, and GenAI features that integrate LLMs into real-time planning workflows.
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