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Key Responsibilities •Design, develop and maintain scalable ETL/ELT data pipelines for large-volume structured and unstructured datasets. •Develop high-performance data processing solutions using Python, PySpark,…
Key Responsibilities Design, develop and maintain scalable ETL/ELT data pipelines for large-volume structured and unstructured datasets. Develop high-performance data processing solutions using Python, PySpark, Apache…
At F5, we strive to bring a better digital world to life. Our teams empower organizations across the globe to create, secure, and run applications that enhance how we experience our evolving digital world. We are…
A senior individual-contributor engineer at FTSE Russell (LSEG) designs and scales index data distribution systems, owning architecture, data modelling, and secure client-facing APIs. The stack centers on TypeScript/Angular/React, Python, SQL, AWS serverless services, PostgreSQL/DynamoDB, and Terraform-driven CI/CD with AI-assisted tooling.
Backend-focused software engineer at an AI consultancy in Izmir who turns LLMs, RAG and agent architectures into production features — building APIs (Python/FastAPI, .NET Core), evals, guardrails and Azure deployments for client projects and the company's own AI SaaS products.
Middle Python developer building and improving AI agents for corporate real-estate and office-management products using LangChain/LangGraph, FastAPI, and vector databases.
Data engineer on a 2-year contract in Singapore to support and enhance an enterprise data analytics platform: designing ETL pipelines, implementing data quality frameworks, and administering, monitoring, and tuning data platforms using integration tools like Informatica/Talend/Denodo and databases such as MSSQL, PostgreSQL, MinIO, and ChromaDB.
Realign LLC is hiring a senior Python Developer in Alpharetta to design, build, and deploy AI-powered applications, backend microservices, and intelligent automation. Day-to-day work centers on Python (FastAPI/Flask/Django), REST APIs, LLMs and Generative AI, RAG pipelines, vector databases, and Docker/CI-CD.
Remote (Sri Lanka) AI/ML engineer who develops, trains, and deploys machine learning models, builds data pipelines, and implements LLM-based solutions such as RAG systems, vector databases, and n8n/LangChain automations. Core stack: Python, TensorFlow/PyTorch, Docker, FastAPI, and MLOps tools.
Job Overview At TE, we strongly believe that data and AI are strategic drivers for future success. We are building a world-class advanced analytics team that will solve some of the most complex strategic problems and…
Job Description Autonomous Network Architect – Mobile & Fixed Design and deliver autonomous network solutions for telecom environments, focusing on network programmability, APIs, cloud-native architectures, and…
Reclutador: Victor Beltran Ubicación de la posición: Mexico Modalidad de trabajo: Híbrido Industria – Sector: Tecnología / Inteligencia Artificial / Cloud Computing / Transformación Digital Tus funciones: Diseñar,…
Overview As a Full Stack Engineer, you will design, build and scale Generative AI applications, turning proof-of-concepts into production-ready solutions. You’ll collaborate across disciplines to deliver AI-driven and…
Overview In this role you will design, build and scale Generative AI-powered solutions within a collaborative, innovative environment. You’ll take concepts from proof-of-concept to production, work across AI-driven and…
Designs and builds AI-enabled enterprise applications and intelligent agents: Java/Spring Boot microservices backends, React/Angular frontends, Python-based GenAI/LLM capabilities, and CI/CD pipelines, owning end-to-end delivery in a pod-based agile team.
Description About CodeNinja CodeNinja is a global software and AI infrastructure company delivering full-stack technology solutions across AI, software engineering, data, and digital transformation. With operations…
Data engineer who acts as a software engineer first, building the core data layer of an AI-driven, agentic data-integration platform: designing multi-tenant data models and schemas, building backend services/APIs, and running batch and near-real-time pipelines across cloud and on-prem environments. Core stack includes Python, SQL/PostgreSQL, Docker, and Kubernetes, with AI/embedding-based workflow
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