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Lead a team building and deploying enterprise data platforms, AI models, and generative AI solutions using Databricks, cloud-native tech, and AI tools like LangChain and Pinecone.
Build and maintain AI agentic backend systems using Python, LangChain/LangGraph, and vector databases to power autonomous workflows and RAG pipelines for business intelligence.
Build and scale internal AI-powered platforms and tools using JavaScript/TypeScript, cloud services, and GenAI features to empower decision-making across McKinsey.
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.
Build and maintain cloud-native data pipelines and vector search infrastructure on AWS, Terraform, and Pinecone to power AI-driven products with multi-tenant architectures.
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 and optimize data pipelines on AWS for clients, focusing on automation, Spark, and CI/CD to enable scalable analytics and business insights.
Build and maintain robust data pipelines and cloud data platforms, preparing data for AI systems and ensuring quality and governance for analytics and agentic use cases.
Build and optimize robust, scalable data pipelines and architectures for enterprise clients, blending hands-on engineering with consulting to turn business needs into actionable data solutions.
Build and optimize AWS data pipelines for enterprise clients, focusing on automation, cloud-native tooling (Spark, Airflow, Terraform), and scalable data platforms to enable analytics and business insights.
Build and maintain CI/CD pipelines, cloud infrastructure, and security hardening for enterprise clients using AWS/Azure/GCP, Linux, and DevOps tooling.
Build and maintain CI/CD pipelines and cloud infrastructure for client projects, focusing on automation, security hardening, and DevOps best practices across AWS, Azure, and GCP.
Build and scale Python backend services with FastAPI for a GenAI SaaS platform, integrating vector databases and collaborating with AI teams to deploy real-time inference workflows.
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 a secure, tenant-isolated AI assistant for real estate title/settlement using Vue.js frontend and Python/FastAPI backend on AWS, integrating vector search and LLM APIs.
Build and scale high-throughput Python backends (FastAPI/Django) and TypeScript/React frontends for global clients, focusing on async APIs, Celery tasks, and PostgreSQL.
Build and scale high-performance Python backends (FastAPI/Django) and TypeScript/React frontends for global clients, focusing on clean architecture, async systems, and end-to-end delivery.
Build and optimize backend services that ingest, index, and serve complex financial data for AI-powered workflows using PostgreSQL, ClickHouse, Kafka, and ElasticSearch.
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