This role is a chance to help shape the future of Virta’s AI-powered coaching experience and contribute to reversing chronic conditions like diabetes and obesity at scale. As a key member of the technical leadership team, you’ll play a central role in evolving Virta's GPT-based chatbot into a powerful platform that supports coaches, engages members, and drives real health outcomes.

Help with developing a connector for a new integration, design and implement a unified data model, convert data pipelines to incremental workloads to improve performance, and create an AI Agent workflow backend that provides tools for LLMs to query a knowledge graph to produce reports and insights for our customers.

This is a technical-first role for someone who’s grown up in engineering, loves building teams and systems, and is ready to lead a full-stack product development org at a mission-driven startup. You’ll partner closely with our founder/CEO on product strategy, while owning the execution: building great software, scaling the team, and embedding generative AI into how and what we build. Since this is a start up, everybody contributes directly.

As an engineer within People.AI ’s Application group you will be tasked with bringing People.AI custom-captured data to life through views and workflows that give reps, managers, and sales leaders superpowers. You will help build first class web applications, embeddable experiences that work seamless in other partner environments, Chrome extensions, and more. As an engineer, you'll be a part of a highly independent and autonomous team.

As a Data Science intern, you will help Addepar automate data extraction from unstructured documents using various machine learning tools and processes. Mentorship from senior machine learning and software engineers will guide your work while providing the opportunity to learn the newest techniques in natural language processes, such as large language models (LLMs), and best practices for the machine learning development cycle.

Lead the design of AI solutions within the Microsoft Azure AI ecosystem, focusing on Microsoft Copilot, Copilot Studio, and Microsoft Fabric integration. Drive the adoption of cutting-edge AI technologies to enhance enterprise productivity and workflows as the AI Innovation & Automation Architect. Collaborate with sales teams to understand client requirements and design tailored solutions, addressing business and technical needs. This position requires travel to internal meetings as needed, up to 10%.

Join one of Sona's core product pods and focus on iterating on their early agentic AI prototypes, powered by the latest LLMs. You will work closely with the Customer team and users to ensure a product that fits their needs. The company is looking for someone with strong professional experience in both Elixir and working with the latest LLMs, with a focus on "getting it shipped" and doing so quickly.

Work with clients to understand their requirements and technical challenges. Develop a technical design for a solution and communicate its value. Act as the lead technical member of the implementation project team, making key technical decisions and keeping delivery on track. Utilize technologies like Kubernetes, AI, and LLMs to develop scalable cloud applications. Stay abreast of industry trends and engage in problem-solving to address complex technical challenges.

We are seeking a Lead - AI Engineer expert to drive AI strategy, architecture, and development. This role requires expertise in LLMs, RAG, multi-agent AI frameworks, vector databases, and AI security. You will lead a team in building scalable AI applications, with a focus on LLM-driven solutions, AI-powered automation, and Conversational AI chatbots.

As part of our AI team, you will partner closely with product development teams to design, build, and implement AI features that will shape the future of data-driven decision-making. Be part of a small, innovative team to build AI-powered, customer-facing features in dbt Cloud. Contribute to backend development and LLM-related projects such as sending requests to LLMs, logging responses, and building evaluation tools.