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Build and maintain scalable data pipelines on AWS and Snowflake, integrating vector/graph databases with AI workflows using Python and SQL.
Leads a team to design and build a scalable AWS/Snowflake-based data platform for manufacturing, supply chain, and engineering data—focusing on ingestion, transformation, and real-time analytics pipelines.
Design and build scalable AI platforms for healthcare, focusing on LLMs, RAG, multi-agent systems, and model routing to improve clinical decision-making and patient care.
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.
Builds AI-assisted data pipelines to parse undocumented industrial codebases into structured documentation using Python, Neo4j, Qdrant, and LLMs.
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.
About IndyKite IndyKite is a pioneer in data trust and AI enablement, building the trust and decision layer for enterprise agentic AI. Powered by a live context graph, the IndyKite platform brings deep contextual…
Build and scale a distributed cloud-security platform in Python, working with Neo4j, ElasticSearch, TimescaleDB, Redis and RabbitMQ across AWS, GCP and Azure.
Builds full-stack web apps on cloud infrastructure for AbbVie’s internal tools, using JavaScript frameworks (Angular/React/Vue), server-side languages (Python/Node/Java/.Net), and databases (Oracle/PostgreSQL/Neo4J/MarkLogic).
Fullstack-разработчик проектирует и пишет корпоративные веб-приложения на Python/FastAPI, Node.js и React, внедряет AI/RAG-решения и интегрирует корпоративные сервисы.
Builds and optimizes large-scale data pipelines and search systems using Python, Spark, and SQL, with a focus on indexing, relevance tuning, and knowledge graphs.
Backend Developer with 3-5 years of experience designing and implementing robust, scalable backend services and microservices using Java/Spring Boot, .NET/.NET Core, Node.js, or Python. Responsible for API development, database management, CI/CD pipelines, and promoting engineering best practices in a financial technology environment.
Builds and maintains robust LLM-based AI agents and RAG pipelines, designs multi-step reasoning workflows, and implements quality evaluation frameworks to ensure reliable, production-grade AI systems.
Senior sysadmin and Python automation engineer building and securing graph-database infrastructure, data pipelines, and Kubernetes clusters.
Build AI agents that model and reason over live enterprise networks to automate security decisions and troubleshooting using Python, graph databases, and cloud-native tools.
Leads AI Agent architecture for an industrial XR platform, modeling complex plant/logistics data into knowledge graphs and building multi-step agent workflows to automate hands-free maintenance and logistics tasks.
Build backend services for real-time cloud and AI security detection/response using Kubernetes, Docker, Neo4j, ElasticSearch, Redis, TimescaleDB, and RabbitMQ.
Builds and secures a cloud runtime intelligence layer for enterprises using AWS, GCP, Azure, Kubernetes, and databases like Neo4j and TimescaleDB.
Build and deploy multi-agent AI systems, multimodal pipelines, and RAG/Graph-RAG for fintech use cases using Python, PyTorch, and Databricks.
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