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Key Responsibilities Own delivery of LLM API integration and SDK patterns used across applications. Set organizational guidance on which LLM to use for what use case and drive delivery of multi-LLM scenarios. Define…
Senior Machine Learning Engineer Description - We are looking for a Senior MLOps Engineer to design, build, and operate the infrastructure that enables machine learning models and large language models to be deployed…
The Senior Data Scientist will lead complex machine learning and generative AI initiatives, including agentic workflows and RAG solutions, to drive business insights and strategic outcomes. The role involves mentoring junior staff, collaborating with cross-functional teams, and ensuring responsible AI practices within a financial services environment.
The AI Engineer will design, develop, and deploy production-grade Agentic AI and Generative AI systems for BMO Capital Markets. The role focuses on building scalable AI platforms, LLM-based applications, and orchestration frameworks to support investment banking and global markets.
Position Summary We are seeking an Intermediate Fullstack AI Platform Engineer to help build production AI agents and agent-backed workflows on AWS. This is a hands‑on engineering role for someone who has built real…
Design and deliver enterprise-scale AI/ML solutions on Azure/GCP, build MLOps pipelines, automate workflows with Terraform/GitHub Actions, and support Generative AI use cases.
About Mind Moves Mind Moves is a women-owned Washington, D.C.-based firm helping businesses and governments to embrace, build and deploy ‘human in the loop’ AI solutions to elevate mission and value. We are pioneers…
The AI Engineer designs and implements AI-based applications using Python, LLMs, and orchestration tools like LangChain. The role involves building scalable, secure architectures on cloud platforms and integrating them into enterprise environments.
The Full-Stack Engineer will design, develop, and support .NET-based web applications and APIs while integrating AI capabilities using tools like Gemini and Vertex AI. The role involves working in an agile environment to optimize application performance and scalability.
The Full-Stack Engineer will design, develop, and support .NET-based web applications and APIs while integrating AI capabilities using tools like Gemini and Vertex AI. The role involves working in an agile environment to optimize application performance and scalability within a global communications group.
The MLOps/Cloud Deployment Engineer will manage the production infrastructure, CI/CD pipelines, and observability for AI and agentic systems in a regulated environment. This role focuses on cloud-native platform engineering, model governance, and performance optimization rather than model development.
The Lead Architect will design and oversee the deployment of enterprise-grade agentic AI solutions on Microsoft Azure. This role involves defining architecture patterns for LLM orchestration, integration, and security while guiding engineering teams through the full development lifecycle.
Build and deploy small language models, vision-language-action models, and AI orchestration layers for in-vehicle infotainment, ADAS, and connected services across edge and cloud.
Senior AI Engineer at RBC building production agentic AI and generative AI systems — including MCP servers, RAG pipelines, and multi-agent workflows — using Python, LLMs, and cloud platforms.
Own the deployment, operation, and reliability of AI-enabled geoscience software platforms, designing CI/CD pipelines, Kubernetes environments, infrastructure-as-code, and observability systems across Azure and AWS.
Design, build, deploy, and continuously improve production-grade LLM-powered agentic AI solutions within enterprise client environments using Python, FastAPI, agent orchestration frameworks (LangGraph, LangChain, etc.), MCP, and context engineering.
The Gen AI Engineer designs and implements retrieval-augmented generation (RAG) pipelines for banking clients using the Azure AI stack and Python-based frameworks. The role focuses on building secure, traceable, and accurate AI systems, including prompt orchestration, guardrails, and vector database management.
This GenAI Engineer role focuses on designing and implementing RAG pipelines and agentic AI solutions for banking clients using the Azure AI stack and Python-based frameworks. The position requires building secure, compliant, and traceable AI systems with a strong emphasis on guardrails, vector databases, and model evaluation.
The AI Solutions Architect will lead the design and implementation of end-to-end AI/ML and RAG systems for banking clients, ensuring compliance with regulatory standards. The role involves defining technical architecture across Microsoft Azure and open-source stacks while mentoring a team and establishing engineering guardrails.
Leads end-to-end design and deployment of production-grade AI/ML and GenAI solutions, focusing on RAG platforms, agentic systems, and secure enterprise integrations using Python, AWS/Azure, and MLOps practices.
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