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Build and own backend services in Node.js/TypeScript, occasionally contribute to React frontends, and design APIs while working with LLM agent systems and observability tools.
Senior full stack engineer building a secure AI-first cybersecurity SaaS platform for SMEs, working across React/TypeScript frontend, Node.js backend, PostgreSQL, Azure cloud, and LLM integrations (OpenAI, Claude) with strong emphasis on secure coding and AI cost optimization.
Build and maintain Python-based backend services and AI-powered chatbots, integrating LLMs and RAG workflows to deliver scalable, production-grade applications.
Hands-on AI Engineer designing, building, and deploying LLM/GenAI solutions covering the full AI lifecycle including RAG pipelines, agentic AI, model training/fine-tuning, and production deployment using Python.
Role Mission Own the translation of business problems into production-ready LLM applications. This role designs the application logic around the model: prompt architecture, context management, tool calling, RAG…
Build and deploy agentic AI/ML applications on AWS for national security missions, using Python, large language models, RAG architectures, and agent orchestration patterns to automate workflows and support decision-making.
Build and deploy scalable ML and GenAI solutions at Amgen, turning prototypes into production-ready services using Python, cloud platforms, MLOps and containerization.
The Lead Data Scientist will architect and develop autonomous AI agents capable of goal setting and decomposition for healthcare applications. The role involves designing planning systems, implementing evaluation frameworks, and ensuring agent reliability using technologies like Python, PyTorch, LangChain, and large-scale ML pipelines.
Design and deploy production-ready generative AI solutions and autonomous agents using Python, LLMs, and frameworks like LangChain, while partnering with MLOps and business stakeholders at a healthcare company.
Develops and deploys AI-powered legal tools by designing experiments, evaluating LLM/ML models, and prototyping agentic systems for legal research, drafting, and decision-making.
Design and deploy production-grade agentic AI solutions using Python, LLMs, and agent frameworks like LangChain/LangGraph, collaborating directly with client engineering and product teams in a client-facing delivery role.
Lead a Data Science & AI team at Synchrony Financial, prototyping and evaluating Generative AI and Agentic AI solutions (RAG, workflow automation, agentic orchestration) across AWS/Azure/GCP while driving readiness assessments and cross-functional delivery.
Directs an enterprise AI/ML engineering organization at McKesson, owning P&L, multi-year technical roadmaps, and AI/ML systems (LLMs, cloud platforms, data architecture) in a regulated healthcare environment.
Designs, builds, and evaluates AI agents and LLM-powered systems (RAG pipelines, tool-use workflows) using Python to automate multi-step research and clinical-support tasks at a medical center.
About this role: Wells Fargo is seeking a Quantitative Analytics Manager. Wells Fargo is seeking a hands-on Manager for oversight of development of Foundation models as well as Gen AI and Agentic applications…
Leads AI-driven software development for healthcare tech, integrating NLP, computer vision, and generative models into scalable systems while mentoring engineers and driving AI-first strategies.
Design and develop Agentic AI applications using LLMs, Neo4j, Knowledge Graphs, and GraphRAG in Python on a 6-month remote contract.
The Principal AI Software Engineer will architect enterprise-grade AI solutions, integrating LLMs, RAG, and agent workflows into high-availability systems. The role involves leading cross-functional teams, setting technical standards for AI development, and optimizing performance and costs across cloud-based infrastructure.
The Technical Architect will design and implement scalable, fault-tolerant AI systems on Google Cloud, bridging the gap between research and production. The role involves leading MLOps lifecycles, defining compute strategies for AI workloads, and mentoring teams to build resilient, cloud-native architectures.
Lead the technical and architectural design of in-house applications for US Regulatory Reporting at RBC, focusing on AI/ML frameworks (LangChain, LlamaIndex, MCP servers), cloud-based microservices, and big data processing to automate reporting workflows.
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