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A Life Sciences Solutions Engineer at a biotech company translating pharma data needs into compliant AI/data systems, collaborating with cross-functional teams to ensure GxP and EU/US regulatory alignment.
Junior/mid-level data engineer working on data pipelines, Power BI dashboards, and information models in a startup, integrating heterogeneous data and contributing to AI solutions on proprietary platforms.
The Lead AI Engineer will build and scale production-grade AI and Generative AI solutions on AWS to modernize core insurance platforms. This is a hands-on engineering role focused on delivering real-world systems rather than pure research.
Senior AI Engineer designing, building, and operating production-grade Generative AI solutions on the Microsoft Azure AI ecosystem—from model selection and RAG architecture through deployment, MLOps, security, and governance.
About the team Digital Enablement is Nexperia's fast-track enabler of AI & Digital use-cases and platform enablement. We operate as one global practice across Nijmegen, Hamburg, Kuala Lumpur, Seremban and…
Data/AI Engineer on a 4-month hybrid contract in Cork, building data solutions using LLMs—specifically RAG, embeddings, and vector databases—applied to unstructured data.
Build and own modular AI workflow operations and evaluation harnesses for an agentic AI platform serving institutional real estate, ensuring output quality meets the bar of senior professionals.
Owns the platform experience—workflow builders, external integrations (email, Slack, API), and internal automation—for an AI company building agentic workflows for institutional real estate.
Data and AI Engineer II at Freeport-McMoRan, a large mining company based in Phoenix, AZ. No day-to-day details or core technologies were specified in the posting.
AI Engineer owning 'Dougie,' an agentic AI harness for institutional real estate workflows — building memory layers, wiring grading into execution, improving agent orchestration (planning, tool use, recovery), and reducing human-in-the-loop time in production.
Hands-on AI Engineer building production agentic workflows for real estate diligence, planning, and execution using LLMs, Python, RAG, and agent frameworks in NYC.
Design and implement enterprise AI agent solutions using Microsoft Fabric, translating business problems into scalable AI specifications while ensuring governance and security compliance.
Advance voice and multimodal AI agents for real restaurant environments, owning modeling problems across prompting, fine-tuning, evaluation, dataset development, and production behavior.
AI Product Engineer at Verifast building LLM-powered agents, automations, and internal tools (primarily with Claude) to automate identity/income/employment verification for property management and fintech clients.
Lead AI Software Engineer at RBC's Global Functions Technology team, designing and building cloud-based applications and AI agentic solutions for US Regulatory Reporting using Java, Python, Spark, LLM frameworks (LangChain, LlamaIndex, MCP), and big data platforms like Snowflake and Databricks.
Build and evolve MCP servers, graph-RAG pipelines, and agentic layers that connect a platform to multiple LLMs (Claude, Gemini) using Python, vector databases, and graph data stores.
AI Engineer building production-grade AI/ML and GenAI solutions (RAG, agents, NL interfaces) on Snowflake Cortex AI, using Python, SQL, and Microsoft Azure in a hybrid Toronto role.
Architect and build AI systems for a AAA sports title in Unreal Engine 5 using C++, implementing team-based decision-making, positional awareness, and realistic athletic behavior.
Builds and evolves MCP servers, tools, and graph-RAG pipelines to expose platforms to LLMs (e.g., Claude, Gemini) using Python, RAG, and vector databases, collaborating with product, data, and QA teams in an agile model.
Build MCP servers and graph-RAG pipelines, integrate multiple LLMs (Claude, Gemini), and deliver production-grade AI solutions in an agile team with product, data, and QA.
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