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Build and lead the internal AI platform: design LLM frameworks, prompt management, evaluation, and observability systems to enable teams to ship AI-powered features reliably.
Develops end-to-end data pipelines for a natural language search platform, managing multimodal data ingestion, vector/text search preparation, and high-load architecture using Python, SQL, Airflow, Spark, Kubernetes, and S3.
Build production-ready AI apps for enterprises using LLMs, RAG, AI agents and workflow automation, integrating them into existing systems.
Lead a team building scalable data pipelines and infrastructure for an AI-driven platform, designing systems for vector search, ML workflows, and real-time analytics using Python, Spark, Kafka, and vector databases.
Lead AI and Python development teams to design, build, and deploy machine-learning solutions in the cloud using Agile practices.
Lead a team to design and deliver Python-based GenAI solutions, guiding architecture, cloud deployment, and responsible AI practices for enterprise clients.
Lead the design and deployment of enterprise-scale AI/ML and LLM solutions, including generative AI, RAG, and knowledge graphs, while mentoring teams and ensuring Responsible AI compliance.
Build and scale enterprise-grade full-stack apps using React, Node.js, and cloud services, integrating AI features like copilots and RAG while ensuring performance and security.
Builds AI-assisted data pipelines to parse undocumented industrial codebases into structured documentation using Python, Neo4j, Qdrant, and LLMs.
Lead AI engagements, design full-stack systems, and deploy production-ready prototypes using React, Python, and RAG architectures for enterprise clients in Kyndryl’s Frisco lab.
Builds full-stack web apps in Python (Flask/Django) with React/TypeScript front ends, integrating LLM capabilities via RAG and processing large datasets with PostgreSQL, ArangoDB, and vector search.
Builds and deploys LLM-powered assistants, RAG pipelines, and agent workflows using Python, TypeScript, and AWS services to deliver secure, scalable GenAI solutions for Amgen’s internal productivity and healthcare applications.
Build and deploy enterprise-grade generative AI systems (LLMs, RAG, agents) for Citi’s operations, integrating models like GPT-5 and Claude into Python services and APIs.
Lead the AI Knowledge Graph product, defining roadmaps and requirements to connect enterprise data into a semantic layer that powers search, analytics, and agentic AI workflows across Cisco’s platforms.
Lead a data-science team to build and deploy ML models that power personalized shopping experiences and recommendation systems for an ecommerce retailer.
Lead the future of healthcare AI at St. Peter's Health! As our Lead AI Engineer, you'll serve as the principal technical leader responsible for designing, building, and scaling enterprise AI solutions that…
Build and deploy full-stack AI applications using OpenAI's ecosystem, from conversational apps to agentic systems, end-to-end in TypeScript/React and Python/Node, with RAG pipelines and enterprise integrations.
Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations. Trusted by global…
Design and implement large-scale data architectures using Databricks Lakehouse, Apache Spark, and Delta Lake, while optimizing cloud costs and governance for global enterprise clients.
Design and deploy production-ready AI systems, including LLM apps, RAG pipelines, and voice AI, for clients across healthcare, ecommerce, travel, and other sectors.
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