科技職缺
職缺列表
AI Engineer (AWS Bedrock is a must)
Remote AI Engineer role building production-grade GenAI systems on AWS for startup clients, focused on RAG pipelines, multi-agent workflows, and LLM-powered backend services. Core stack: AWS Bedrock, OpenSearch, Lambda, SageMaker, Python, LangChain/LlamaIndex.
AI Product Engineer
Design, build, and ship production AI systems end-to-end — architecting RAG pipelines, agentic workflows, and LLM integrations using Python/TypeScript, FastAPI/Node.js, and modern AI coding tools like Cursor or Claude Code.
Technical Product Manager – GenAI Programmes
Lead end-to-end delivery of enterprise GenAI use cases from POC through production MVP, translating business objectives into technical direction around LLMs, RAG, agents, embeddings, and vector databases while managing senior stakeholders across parallel AI streams.
Software Engineer II
Full-stack Software Engineer II on Microsoft's CEAI Data Science & AI Engineering Platform team in Hyderabad, building enterprise-grade AI-powered web applications. Combines full-stack development (React/Angular, C#/.NET/Python/Java/Node.js) with Generative AI/LLM integration on Microsoft Azure.
Senior Software Engineer, MLOps/SRE
Senior MLOps/SRE engineer on Roku's Advertising Performance team, designing and operating cloud-native ML infrastructure on GCP and AWS using Kubernetes, Spark, Airflow, Ray, and MLflow to power large-scale, low-latency training and inference for ads optimization.
Senior Software Engineering Manager – Manufacturing Intelligence, Agentic Systems & Physical AI
Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there is no telling what you…
ASSOCIATE, DATA ENGINEER
Build and maintain Cresset's data platforms on AWS, Matillion, DBT, Databricks, and Snowflake at this multi-family office and private investment firm. The role blends data warehousing, BI, and AI/LLM pipeline work including MCP servers, RAG, and vector databases.