Senior AI Engineer
Develop and implement AI solutions by designing proof-of-concepts and translating them into minimum viable products. Collaborate with cross-functional teams to optimize AI models and integrate capabilities into existing systems.
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Develop and implement AI solutions by designing proof-of-concepts and translating them into minimum viable products. Collaborate with cross-functional teams to optimize AI models and integrate capabilities into existing systems.
Design and build server-side APIs and support tooling to manage large-scale data operations and backups. Utilize AI-assisted development tools to accelerate implementation while ensuring security, performance, and correctness.
The Staff Software Engineer will lead the implementation and integration of Generative AI solutions into production software to solve complex business problems. They will also mentor engineering teams on AI adoption and collaborate with cross-functional stakeholders to deliver scalable, AI-enhanced features.
Lead complex, end-to-end AI deployments and manage customer relationships throughout the engagement lifecycle. Architect multi-agent solutions, design personalized resource packs, and mentor junior engineers to ensure high-quality deployment standards.
Lead complex, multi-system AI deployments end-to-end, managing the full engagement lifecycle from technical discovery to production. Architect multi-agent solutions and design personalized resource packs while mentoring junior engineers and driving strategic intelligence loops.
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You will design and build next-generation cloud-native EHR platforms while shaping technical architecture and product direction. The role involves operating at the intersection of distributed systems, cloud infrastructure, and applied AI to create scalable healthcare solutions.
You will architect and implement scalable AI platform services while directly applying large language models to build intelligent product features. Additionally, you will manage model lifecycle, infrastructure, and integration strategies to ensure high performance and security across the platform.
Design and maintain a robust platform for creating and managing intelligent AI agents with a focus on multi-agent coordination. Collaborate with cross-functional teams to integrate LLMs and orchestration frameworks while ensuring system scalability and data privacy compliance.
You will design and maintain a platform for creating and managing intelligent AI agents with a focus on multi-agent coordination. Additionally, you will integrate various LLMs and develop evaluation frameworks to ensure system-level performance and scalability.
Lead the design, development, and deployment of intelligent, user-facing AI features and products. Collaborate with cross-functional teams to integrate LLMs and ensure the scalability and performance of AI-powered solutions.
You will architect and implement scalable AI platform services while directly applying large language models to deliver intelligent product features. This role involves building robust backend systems, managing model lifecycles, and ensuring high performance and security across the AI infrastructure.
Lead the design, development, and deployment of AI-powered features while orchestrating multiple LLMs to deliver personalized user experiences. Collaborate cross-functionally to translate user needs into technical solutions and ensure the scalability and performance of AI products.
You will own the inference and orchestration layer that powers AI interactions, ensuring high reliability and low latency. Your role involves building production systems, designing inference pipelines, and managing monitoring and incident response.
You will build end-to-end product features and design agent workflows that handle planning, tool use, and failure recovery. You will collaborate with ML and backend teams to integrate LLMs and memory into reliable, production-grade systems.
The Senior AI Engineer will design, build, and deliver AI-powered features by integrating large language models into production systems. They will collaborate with ML engineers to develop end-to-end solutions, optimize prompts, and ensure the scalability and reliability of AI applications.
You will develop, deploy, and optimize AI agents while integrating them with external systems to solve practical customer problems. Additionally, you will collaborate with customers and internal teams to gather requirements, conduct demos, and provide technical guidance for successful AI deployments.
You will design, build, and operate LLM-powered agents that coordinate engineering workflows, surface project risks, and generate structured deliverables. Additionally, you will own the agent orchestration layer and collaborate with cross-functional teams to integrate AI features into hardware development platforms.
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You will lead the design and delivery of agentic systems that orchestrate tools, data, and policies to solve complex business workflows. This involves building modular components, ensuring system reliability through observability, and collaborating with enterprise clients to translate business processes into production-ready AI solutions.
The Senior Security Engineer will own the end-to-end security of AI systems, including threat modeling, adversarial testing, and implementing security controls across the ML lifecycle. They will collaborate with cross-functional teams to embed security into AI development pipelines and ensure compliance with regulatory frameworks.
The GTM Engineer will architect and scale AI-powered growth systems across sales, marketing, and product functions. They will lead the development of AI agents and workflows to automate the customer lifecycle and provide actionable growth signals.
You will build and integrate AI-powered features into production systems while improving the reliability, latency, and quality of existing AI workflows. The role involves taking ownership of the full development lifecycle, from conceptualizing ambiguous product ideas to deploying robust, production-ready software.
You will build and integrate AI-powered product features from concept to production while improving the reliability and performance of existing workflows. The role involves designing LLM-based systems, implementing validation logic, and maintaining high-quality AI outputs within a fast-paced startup environment.
Evaluate and analyze LLM performance while architecting and building inference and training pipelines. You will contribute to hands-on design, model training, and deployment strategies within a technical greenfield project.
You will own and extend the backend systems that power SqlDBM's AI capabilities, including AI-assisted data modeling and context-aware intelligence. You will also develop and maintain AI pipelines, API layers for enterprise integration, and Model Context Protocol servers.
The role involves joining a talent database to be matched with software development opportunities for various global clients. You will provide expert-level AI engineering services while maintaining a professional and agile development process.
Join a talent network to be matched with software development opportunities based on your skills and experience. Maintain confidentiality while your profile is shared with companies seeking expert AI engineering talent.
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The AI Software QA Engineer is responsible for testing, validating, and ensuring the quality of AI-enabled systems and backend APIs. They will design and execute automated test cases while collaborating with developers and AI engineers in an agile environment.
You will build and scale the AI Agent platform to handle high-volume, real-time conversational workflows across multiple channels. This involves designing APIs, managing the full software lifecycle, and collaborating with cross-functional teams to improve system performance and reliability.
Design and build internal AI productivity tools, including coding assistants and knowledge retrieval systems, to improve engineering efficiency. Integrate AI capabilities across the software development lifecycle and experiment with emerging technologies like LLMs and AI agents.
You will build AI-powered internal tools, including coding assistants and workflow automation systems, to improve developer productivity. You will also collaborate with engineering teams to identify technical pain points and implement LLM-driven solutions.
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