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Hands-on data engineer building production data pipelines and agentic AI components (RAG, tool-calling agents) for clinical and non-clinical data at Lilly, using Python, Spark/PySpark, Databricks, and LLM frameworks in a regulated pharma environment.
The Junior AI Engineer will build and maintain LLM-powered applications, including RAG pipelines and chatbots, while integrating AI features into existing logistics systems. The role involves fine-tuning open-weight models and developing front-end interfaces using React and Next.js.
Build AI-powered features like search, recommendations, and generative AI tools for a healthcare marketplace, spanning models, APIs, and user interfaces.
Build and maintain Python backend services and APIs for ML and Generative AI applications—including LLM, RAG, and AI agent workflows—deployed into cloud/GCC environments with a focus on Responsible AI controls and production support.
Build and deploy ML models from scratch (e.g., Random Forests, Neural Networks) to detect spam and threats, using Python and cloud infrastructure without managed services.
Machine Learning Engineer building and maintaining ML-powered features for a healthcare platform, working across the AI stack including RAG, fine-tuning, and agentic workflows in a cloud environment.
AI Platform Engineer at DXC Technology in Mexico City designing and building the AI foundation for a next-gen enterprise CPQ platform, using Python, LLMs (Claude/GPT), vector databases, and MCP to transform a legacy application into an AI-native solution.
Design and build AI-native multi-agent systems for sales workflows using LLMs, RAG, and agentic frameworks while acting as product owner—managing backlogs, roadmaps, and stakeholder alignment.
Build and deploy generative AI features and full-stack apps to modernize Barclays’ platform, using Python/Java, cloud-native tools, and enterprise-grade security.
Builds and deploys AI-driven systems (RAG, agents) for Thomson Reuters’ investigative platform CLEAR, integrating AI into full-stack web apps, APIs, and enterprise workflows for legal/tax/compliance domains.
Build high-performance software for silicon testing and debug using LLMs, graph ML, and reinforcement learning to improve yield and failure analysis in AI and compute platforms.
Lead Data Engineer (Permanent, London on-site 4 Days) - Sponsorship is not available for this role A high-growth AI software company is looking for a Lead Data Engineer to own and scale the data foundations behind an…
Build and enhance mission-critical software for national security systems using Python, cloud-native tools, and AI-driven development workflows.
Senior Technical Architect leading complex Data 360 (Salesforce Data Cloud) implementations—designing data integration, ETL, and CDP solutions as a strategic advisor to enterprise customers while mentoring internal teams.
Lead the design, development, and deployment of production-grade generative and agentic AI systems at a large financial services firm, using AWS, RAG architectures, vector databases, and LLM orchestration tools while bridging business stakeholders and engineering teams in Dallas.
Builds AI-powered automation solutions for internal business processes (Finance, HR, Logistics) by designing agentic systems, integrating LLMs/RAG, and deploying scalable production-grade models while ensuring security, governance, and observability.
Architect, build, and scale backend services for an agentic AI platform at Adobe, designing APIs, data pipelines, and agent orchestration infrastructure using Python, LLMs, vector databases, and cloud platforms.
This senior full-stack role involves building and maintaining agentic-first software systems where AI agents draft code based on specifications you write. You will work across a Python/FastAPI and React stack, managing Kubernetes-based LLM infrastructure and CI/CD pipelines in secure environments.
Netguru is seeking a Senior Python Developer to build an AI agent for image processing systems. This is a full-time, 3-month freelance contract requiring expertise in Python, agentic frameworks, LLM SDKs, and vector databases.
The AI DevOps Engineer will design, automate, and optimize cloud-native infrastructure on AWS while integrating AI-powered tools to enhance CI/CD pipelines, observability, and operational efficiency. The role involves collaborating with engineering and AI teams to support scalable, intelligent cloud platforms and MLOps workflows.
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