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Fullstack developer at RIS group building secure corporate digital products from scratch — intranet solutions, corporate service integrations, and LLM-based AI/RAG assistants. Day to day: Python/FastAPI and Node.js backends, React/Next.js frontends, plus PostgreSQL, Docker, and API integrations.
Senior Software Developer leads end‑to‑end development of Alice’s internal malware research platform, collaborating with researchers to build Python async, agentic LLM tooling and ensure high adoption while mentoring the team.
Own the architecture of LSports' large-scale real-time sports data platform on GCP (GKE, Kafka, GitOps) and build its agentic AI ecosystem — designing reliability, security, and FinOps for the cloud platform while defining how AI agents are orchestrated, evaluated, and governed in production.
Senior Software Engineer at Cryoport Systems leads technical initiatives and architecture for core supply-chain applications, including AI-powered features like LLM integrations and RAG pipelines, while mentoring engineers. Stack includes Ruby/Rails, Java, Python, React, AWS, Docker, and AI tooling like LangChain and vector databases.
Full-stack AI Engineer on J.D. Power's Innovation Crew, building backend services, REST APIs, Snowflake data connectors, and frontend components for AI agent pilots and the internal Power Agents library. Hands-on work with frontier model APIs and agentic frameworks like LangGraph and CrewAI; remote across USA, Canada, Europe, or Australia.
Associate-level full-stack developer at PwC Philippines (Makati) building AI-powered web applications for client engagements — integrating LLM APIs (OpenAI/Anthropic), RAG and vector search, plus React/Vue frontends and Python/Node/TypeScript backend services, working alongside consultants and data scientists.
Sidram Technologies is hiring a Python Developer (GenAI/LLM) for its client Citi Bank in Mississauga. The role builds and deploys enterprise GenAI applications - RAG pipelines, prompt engineering, and agentic AI - using Python, LangChain, FastAPI, Vertex AI/Hugging Face, vector databases, Kubernetes, and CI/CD/MLOps tooling.
Senior full-stack and operations engineer at Flyp working on a UK residential property platform: roughly half the role is production health, incident response, and CI/CD upkeep, the rest is building features with TypeScript, React, Node.js, and PostgreSQL on GCP, including Agentic AI/LLM integrations. Fully in-office in Cape Town.
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.
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.
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.
Freelance senior Python backend developer for an AI project in the Milan area: building backend services with FastAPI, agentic multi-turn RAG architectures using LlamaIndex and Gemini, and a PostgreSQL (pgvector/FTS) + Redis data layer. Hybrid, with 2 days/week on-site in Segrate, engaged through the Shakers talent marketplace.
Full-stack engineer designing and scaling Generative AI solutions (RAG, intelligent agents) for a UK technology organisation, moving proof-of-concepts into production-grade platforms. Core stack: Python/FastAPI or TypeScript/Express backends, React frontends, AWS/Azure, Docker/Kubernetes, and vector/SQL databases. Active UK SC clearance required.
AI & Python Developer building GenAI and agentic RAG systems: designing scalable back-end services with Python/FastAPI, LlamaIndex, Gemini, PostgreSQL (pgvector, FTS) and Redis. Based in Segrate (MI), hybrid with 2 on-site days per week; day rate up to €260, with final selection involving the client.
Hands-on AI Architect at PA Consulting who owns delivery architecture for client engagements building AI agents, intelligent workflows, digital products, and platform modernizations. Works directly with clients using Python, TypeScript, cloud platforms (AWS/Azure/GCP), agent frameworks like LangChain/LangGraph, and retrieval tech such as pgvector and Elasticsearch.
Hands-on AI engineer in PA Consulting's Digital Products & AI practice: builds and ships production AI agents, retrieval pipelines, and modernized platforms for consulting clients across industries. Works client-facing from discovery through deployment using Python, TypeScript, cloud (AWS/Azure/GCP), and LLM orchestration tools like LangChain and LangGraph.
Senior ML engineer builds and refines AI agents and RAG systems for internal document search at a large Russian company, focusing on prompt engineering, quality metrics, and production safeguards.
Senior GenAI developer designs and implements corporate AI solutions like agents, RAG pipelines, and automations for a large mining-industry company using n8n, PostgreSQL, and Python.
Builds and deploys production-grade GenAI applications using LLMs, RAG pipelines, and agent frameworks like LangChain/LangGraph, plus full-stack Python/.NET/React systems.
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