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Builds AI-powered agentic applications by implementing LLM tooling, RAG pipelines, and vector search, integrating with enterprise systems, and ensuring safety/testing. Core tech: Python, TypeScript/Node.js, Java, LangChain, vector DBs (pgvector, Pinecone).
Build AI-powered applications using Java full-stack, Python, and TypeScript, implementing agents, RAG pipelines, and vector search for rapid prototyping and production systems.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating enterprise APIs and ensuring robust testing and safety.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating APIs and cloud services while writing clean, testable code and CI/CD pipelines.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; implement agents, prompts, and APIs while owning full-stack development and CI/CD.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; implement agents, prompts, and CI/CD while integrating enterprise APIs and ensuring safety.
Build and deploy LLM-powered tools, RAG systems, and agentic workflows for autonomous aircraft systems, focusing on retrieval quality, tool integrations, and production-grade AI infrastructure on Kubernetes.
Design and build scalable data pipelines using Databricks, Snowflake, and Spark, leading architecture decisions and optimizing performance across AWS/GCP/Azure for client projects.
ML engineer builds and optimizes RAG pipelines, fine-tunes VLM for technical docs, and prepares on-prem LLM/VLM inference for an AI platform serving engineers.
Embedded AI Engineer who designs, builds, and deploys production AI systems for B2B clients in private equity, lending, real estate, and SaaS, bridging business needs with technical execution using LLMs, RAG, and agent frameworks.
Design and teach a next-gen data platform for a fintech SaaS that unifies due-diligence data from 150+ countries, migrating from SQL Server to PostgreSQL and adding AI-native features like vector search and semantic matching.
Build and deploy AI-agent systems for enterprise clients, owning the full lifecycle from discovery to production using Python, FastAPI, and agent frameworks like Strands.
Maintain and tune a SQL Anywhere 17 production database, then migrate it to PostgreSQL 18 while improving query performance, schema quality, and reliability for a global dealership management system.
Build and maintain Azure infrastructure as code (Bicep/Terraform) to migrate and run a multi-tenant SaaS platform for dealership management, including AVD, databases, and CI/CD pipelines.
Build and improve AI agents that automate accounting production for small businesses, using TypeScript, NestJS, and LLM APIs in a monorepo.
Lead a team of ML engineers and architects at an AI-first cloud services company, owning hiring, team growth, and complex customer engagements while shaping AI/ML architectures and driving pre-sales.
Build and ship production-grade AI features (LLM integrations, RAG, agents) for an iGaming affiliate platform, turning prototypes into scalable, high-load services.
Senior AI Engineer builds voice and agentic AI systems, designing and deploying conversational agents and AI-driven workflows.
Build AI-powered automation tools and agentic systems to streamline Apple’s engineering workflows, using Python, LLMs, and modern web frameworks.
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