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【思邁智能】後端工程師 - (Django) Backend Engineer
▋【工作內容】 開發公司相關應用產品與 API 開發可用於公司既有產品之 AI 技術工具 ▋【具備條件】 熟悉 Python, Django 熟悉 ORM 資料庫建置 熟悉 Django REST framework 熟悉 Celery 熟悉 Git, Github 熟悉 Docker 習慣使用 ChatGPT, Claude, Copilot 協作 3 年以上 Django相關使用經驗 3 年以上 Python相關使用經驗…
AI 應用工程師
工作內容 1. 負責公司內部 AI 應用開發及維護，如 AI 助理、AI Agent、知識庫及自動化流程。 2. 使用 Python、API 等方式進行資料處理及系統串接。 3. 整合公司內部文件、SOP、Excel、PDF 及系統資料，建立 AI 查詢及應用工具。 4. 建置及優化 RAG、Prompt、AI Agent 及相關應用流程。 5. 與業務、工程、生產及管理單位溝通需求，將實際工作流程轉化為 AI 應用。 6.…
Voice AI Engineer
Builds real-time AI voice, WhatsApp and chat agents for timepay.ai's business customers: designing conversation flows and wiring STT, LLM and TTS into low-latency streaming pipelines with Pipecat, LiveKit, Python, WebRTC/SIP and PostgreSQL/Redis, then testing and tuning agents for natural, fast conversations.
Senior AI Engineer
Senior AI Engineer at Scrums.com acting as a Forward Deployed Engineer: partnering with global clients to turn business problems into production AI solutions (assistants, RAG search, agents), integrating models like OpenAI/Anthropic with client data, and building full-stack apps in the client's tech stack. Hybrid in Johannesburg on a 12-month contractor engagement.
Associate AI Engineer
Associate AI Engineer at Emplay builds LLM-powered features, RAG pipelines, and conversational AI applications using Python (FastAPI/Flask), LLM APIs (AWS Bedrock, OpenAI, Anthropic), and agent frameworks like LangChain, deployed on AWS services such as Lambda, S3, and DynamoDB. Remote role for candidates with 1–2 years of experience.
Backend & Integrations Engineer (iris)
Builds and owns the Google and Meta integrations at the core of iris, a patient-growth platform for independent clinics in India: OAuth, Google Business Profile/Ads, WhatsApp/Instagram/Meta APIs, plus LLM agents and RAG, on an event-driven Python/FastAPI backend running on AWS (Docker, Lambda, EventBridge).
LLM & AI Agent Engineer cum Manager
Builds and manages LLM-powered sales agents — multi-agent workflows, RAG pipelines, and proposal-generation features — for LeadsPipe, an AI sales co-pilot for enterprise and EPC firms. Day to day: Python agent development, prompt chains, evals, and optimizing latency/token cost across LLM providers.
Data Scientist ( AI / ML with GCP)
Agentic AI / GenAI engineer (hired under a Data Scientist title) who designs and deploys secure, production-grade AI agents on Google Cloud. Day to day: Python/FastAPI services, RAG pipelines over vector databases, prompt/tool engineering, LLM evaluation, and MLOps/LLMOps on Vertex AI and Gemini. 6+ years experience required, 3 in GenAI/LLM.
AI Agent / LLM Engineer
Build production LLM agents for Indian D2C brands — customer support on WhatsApp, order tracking, recommendations and ops automation — designing agent architecture with tools, guardrails, RAG and evals. Uses Python/TypeScript with integrations to Shopify, CRMs and catalogues; works directly with the founder.
Senior Associate AI Engineer
Build and ship production LLM features at Emplay: designing GenAI agents, end-to-end RAG pipelines, MCP servers, and multi-region AWS infrastructure, with Python (FastAPI/Flask) backend services, secured APIs, and CI/CD. Remote role for 2–3 years' experience, paying ₹10–14 LPA.
Lead- AI Engineer
Lead AI Engineer at Emplay designing and shipping production LLM-powered agents, RAG pipelines, and multi-agent orchestration on AWS. Day-to-day spans Python backend services (FastAPI/Flask), vector search (OpenSearch/Pinecone/pgvector), third-party CRM/API integrations, and owning CI/CD and cloud infrastructure reliability.
AI Engineer (LLM / Python)
Designs, builds, and operates LLM-powered features (assistants, intelligent search, summarization, agents) for a healthcare compliance platform, taking them from prototype to production. Core stack: Python/FastAPI, OpenAI/Anthropic/Azure OpenAI APIs, RAG with vector databases, Docker/Kubernetes and GitHub Actions on Azure/AWS, alongside an existing PHP/Node platform.
AI Engineer (w/m/d)
Vordenken, verbinden, erreichen: Entlang dieser Werte denken wir über die Grenzen des Machbaren hinaus und schaffen so geniale Produkte und Lösungen für Batteriesysteme, Schweißtechnik und Solarelektronik. Unser…
GenAI Fullstack Engineer
Marlabs, an AI and digital solutions consulting firm, is hiring an onsite GenAI Fullstack Engineer in Englewood Cliffs, NJ to build enterprise apps pairing Java/Spring Boot backends with Generative AI — LLM integration, RAG pipelines, vector databases, and Python/FastAPI services deployed via Docker and CI/CD.
Fullstack Developer Pleno - REMOTO
Verity, a digital transformation and engineering consultancy in Brazil, seeks a mid-level fullstack developer to build backend services, REST/GraphQL APIs, and cloud integrations behind AI-driven prototypes and MVPs. Core stack: Node.js and/or Python, Azure/AWS/GCP, LLM/agent orchestration, SQL/NoSQL databases, and Docker.
Staff Software Architect, Robotics & AI
Staff Software Architect leading system design for Divergent's Robotics & AI team: architecting multithreaded C++/Python systems spanning real-time robotics control, planning/optimization, and generative AI agents — including operator GUIs, robotics stack integration (ROS/ROS2, MoveIt), and CI/CD with containerized deployment at scale.
Generative AI Applications Engineer (Agents & RAG)
At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the…
Staff Machine Learning Engineer - Agentic AI
ELLKAY started out providing connectivity solutions to laboratories and within a few years, grew to also provide data management solutions to ambulatory organizations. ELLKAY is now a trusted data management partner in…
AI Full-Stack Engineer
Build end-to-end AI tools for internal teams: from data pipelines and LLM logic to backend, UI, and deployment, using modern AI stacks and coding assistants.
AI Engineer
AI Engineer at Nologin, a consultancy that designs and implements AI solutions for clients across sectors, working on long-term projects building end-to-end systems. Day to day involves developing LLM-based apps — RAG systems, agent frameworks (LangChain, LlamaIndex, LangGraph, MCP) — with Python, REST APIs, Docker and Linux, in a hybrid model from Zaragoza or Madrid.