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ApplyAZ seeks a full-stack engineer to own its stack end to end: building Next.js/TypeScript frontends, Node/Python backends on AWS, and AI agents (LLM/RAG, Playwright browser automation) that book appointments and fill student applications. Emphasis on Cursor, GitHub workflows, CI/CD, and post-launch ownership.
Senior fullstack engineer at a fast-growing AI company, building production AI features end to end: React/TypeScript on the frontend, Python/FastAPI on the backend, spanning APIs, data, LLM integrations, streaming interfaces, and document-heavy UIs with real ownership of architecture and product.
Lead Architect at PALO IT LABS in Paris, driving AI-first engineering initiatives with the Gen-e2 methodology — defining reference architectures and CI/CD guardrails, leading delivery from discovery to launch, and mentoring teams using GitHub Copilot, OpenAI API, LangChain and cloud platforms (AWS, GCP, Azure).
Lead technical expansion into the German market by designing Generative AI architectures (LLMs, RAG) for enterprise clients. You will manage pre-sales, conduct workshops, and ensure technical feasibility using Python, LangChain, and cloud/on-premise infrastructures while navigating EU regulations like the AI Act.
A remote 1099 contract Solutions Architect who designs, deploys, and maintains AI-powered applications (RAG agents, model serving) running natively on Azure Databricks serverless for higher-education clients. Core tech: Databricks Apps, Unity Catalog, Databricks SQL, MLflow, LangChain/LlamaIndex, Python, FastAPI/Streamlit, and OAuth.
Senior full-stack engineer responsible for designing and building production services using C#, Python, and Angular. The role focuses on platform engineering and AI governance, integrating LLM-backed capabilities using AWS services like Bedrock and SageMaker.
Senior software developer in Toronto building web applications and REST API platforms (Apigee/APIM), translating specs into tested, production code. Core stack is React, TypeScript, Node.js/Next.js and RESTful APIs, with heavy AI/ML work using Python, LangChain, LangGraph, RAG, Airflow and PySpark on Azure.
Infor is hiring a senior engineer to build large-scale data pipelines with PySpark on AWS EMR (on EKS) and Delta Lake, and to develop LLM-powered agentic AI features (tool calling, RAG, human-in-the-loop workflows) that automate work on their platform. Core stack: Python, PySpark, SQL, AWS, Kafka, and LLM frameworks like Bedrock/LangChain.
Senior AI Engineer at Travel Booster will own AWS cloud infrastructure and Azure DevOps CI/CD pipelines, refactor PowerShell, Python and JavaScript scripts, and lead AI/LLM integration across development, QA, and support, building internal agents and automating deployments.
A Python AI Developer at Ayesa Digital designs, develops, and integrates generative AI solutions built on large language models, intelligent agents, and scalable AI architectures for production environments. Core stack: Python, LLMs, and agent frameworks like LangChain, LangGraph, and Google ADK, with Git-based agile teamwork.
Forward Deployed Engineer at a Data and AI consultancy building production data platforms and LLM applications. You will implement components like data pipelines and AI agents, primarily using Databricks, Python, and SQL within client environments while working autonomously on assigned features.
Designs, builds, and operates production-grade agentic AI applications that automate and optimize AI-factory operations across Firmus's Model-to-Grid platform. Day to day: building LLM agent orchestration, RAG pipelines, and tool integrations using Python, agent frameworks like LangGraph/LangChain, vector databases, and Kubernetes-based observability and evaluation tooling.
Senior Data Engineer designing and building scalable Azure data solutions and Applied AI projects for clients in finance, energy, mobility, and healthcare, acting as the technical point of contact in multidisciplinary consulting teams. Core stack includes Azure, Databricks, Apache Spark, streaming, and LLM tools like LangChain and OpenAI.
At Techonomy in Rotterdam you build and maintain data and AI solutions for clients — from ELT pipelines and data warehouses to production-ready AI systems — while contributing to an internal toolkit built on LangChain, dbt, Python and Terraform and embracing agentic engineering.
Designs, integrates, and deploys agentic AI applications on the ReadiChat platform in support of federal mission workflows — building agent definitions, orchestration workflows, AI testing/evaluation suites, and mentoring agent creators. Core stack: Python/JavaScript/TypeScript/Java, LLMs and orchestration frameworks (LangChain, LangGraph, etc.), Docker/Kubernetes, cloud AI services, and DevSecOps
Full-stack engineer at KPMG's Trusted AI Centre of Excellence in Singapore, integrating Generative AI (LLMs, embeddings, vector DBs, LangChain/LlamaIndex) into enterprise applications, building Python backends and TypeScript/Next.js frontends, and owning cloud infrastructure with Terraform and DevOps practices.
Summer 2027 internship (June-August, 5 days/week in office in San Jose) at Veeam, working on Go backend and automation on Kubernetes/AWS, building and evaluating AI agents for security analysts, and hardening container/vulnerability security. Open to rising juniors/seniors or grad students comfortable in Python, Go, or Java.
CGI is hiring an Azure DevOps Engineer in Plano, TX to design, automate, and operate secure Azure cloud infrastructure and CI/CD pipelines, including Kubernetes/AKS platforms and production GenAI/LLM workloads, in partnership with software, data, AI, and security teams. Core stack: Azure/AKS, Terraform/Bicep, Azure DevOps/GitHub Actions, Python, and observability tooling.
Senior backend engineer who owns the full backend lifecycle at an AI-first product company: designing scalable Python/FastAPI services and REST APIs, integrating LLM/AI services with PostgreSQL, Redis and vector databases, deploying with Docker/AWS, and mentoring junior developers. Full-time on-site in Gurugram.
Design and deploy advanced agentic AI systems for life-sciences use cases like clinical trials and drug discovery, using LLMs, NLP, and multi-agent frameworks on AWS.
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