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Build and optimize the core search engine behind Amazon OpenSearch by contributing to Apache Lucene and OpenSearch, improving performance and scalability for distributed log analytics and search workloads.
Lead the design and delivery of scalable AI and data platforms, from petabyte-scale lakehouses to production GenAI solutions, using Python, Spark, Databricks, and cloud services.
Lead a team to architect and deliver scalable digital banking platforms using Java, Spring Boot, and microservices, while embedding AI tools to boost engineering productivity and code quality.
Build and own full-stack AI applications for Amgen’s AI Studio, integrating LLMs, RAG, and automation into production systems using modern JavaScript/TypeScript, Python, and cloud services.
Build and own full-stack AI-enabled applications for Amgen’s AI Studio, integrating LLMs, RAG, and automation into production healthcare systems using modern web and cloud technologies.
Build and deploy LLM-powered assistants, RAG apps, and AI agents on enterprise platforms like ChatGPT Enterprise and AWS Bedrock, using Python, TypeScript, React, and cloud-native tooling.
Build, deploy, and monitor ML models and MLOps pipelines on AWS for forecasting and GenAI apps in a biotech setting.
Build full-stack web apps with React/Node, integrate LLMs and RAG pipelines, and deploy scalable search using Elasticsearch on AWS/Azure.
Designs and deploys production-grade generative AI systems on Databricks for enterprise clients, focusing on RAG pipelines, LLM orchestration, and vector search while leading technical delivery.
Build and own Supabase’s marketing measurement stack: run incrementality tests, media mix models, and attribution to guide budget allocation and revenue growth using SQL, Python/R, and AI tools.
Builds and deploys AI-powered solutions (LLMs, RAG, agentic systems) for insurance underwriting, operations, and customer workflows, focusing on production-grade integration, security, and observability in a regulated environment.
Senior Software Engineer, Intelligence Department: Engineering Location: Remote - USA Compensation: $170K – $200K Employment Type: FullTime The Problem As Flock scales its investigative platform, building capabilities…
Builds cloud-native data pipelines and RAG architectures for LLM systems using Databricks, Spark, and vector search on Azure/GCP.
Build and optimize AI models and infrastructure for a company focused on AI-driven solutions.
Build and tune AI agents, retrieval, and personalization pipelines for a next-gen fitness app’s voice-driven assistant using LangGraph/LangChain, FastAPI, and RAG.
Designs scalable backend APIs and microservices in Node.js, integrating AI capabilities like LLMs, RAG, and vector search for enterprise applications, with a focus on production reliability and real-world tooling.
Build and improve production AI systems using LLMs and RAG pipelines, integrating them with backend services and evaluating performance.
Developer Relations Location: Remote Department: General Developer Relations About Arango: Arango delivers a unified, natively multimodel contextual data platform that powers AI agents, assistants, and applications…
Builds scalable Node.js/TypeScript backend services that integrate LLMs, RAG pipelines, and vector search for enterprise AI features like chatbots and intelligent Q&A.
Build full-stack web apps and integrate AI features using modern stacks (React, Node.js, Python, Java/Spring Boot) and cloud platforms (AWS/Azure/GCP), while leveraging AI coding assistants daily.
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