AI Solutions Architect Jobs

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Run technical discovery, design solutions, and lead POCs alongside Account Executives to close deals, then own onboarding to get customers to first value fast. Build and implement workflows within V7 Go; combining prompt engineering, data pipelines, and integrations to solve real customer problems across document processing and more. Act as the primary technical contact for accounts, handling complex challenges and spotting expansion opportunities as customers scale. Manage up to 10 concurrent projects while feeding customer insights back to product and engineering.

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Run technical discovery, design solutions, and lead POCs alongside Account Executives to close deals, then own onboarding to get customers to first value fast. Build and implement workflows within V7 Go; combining prompt engineering, data pipelines, and integrations to solve real customer problems across document processing and more. Act as the primary technical contact for accounts, handling complex challenges and spotting expansion opportunities as customers scale. Juggle up to 10 concurrent projects while feeding customer insights back to product and engineering.

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As a System Architect, you will own the end-to-end architecture, system definition, and strategic implementation for the entire portfolio of robotic systems, collaborating closely with executive leadership, technical leads, and the Product Manager to ensure efficiency. Responsibilities include translating complex strategic goals into global system-of-systems designs and defining the overall system architecture strategy across the enterprise. You will ensure all systems meet defined needs through verification of scope, complex simulations, and precise system sizing to guide major technical investments. Coordination and technical leadership involve managing large multidisciplinary engineering organizations and providing overarching technical leadership across cross-functional design efforts to ensure long-term performance, robustness, and strategic reliability. Additionally, you will govern system integration standards and validation processes, manage specification by ensuring architectural prerequisites are met, and drive multi-system architecture reviews for enterprise design consistency. You will also implement and institutionalize processes to enhance requirements traceability, system documentation standards, and validation workflows across the engineering organization.

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Design and develop AI applications primarily in Python, run evaluations to validate models, and package solutions for Kubernetes, AWS, or adapt them to customer on-premises clusters. Lead discovery sessions with customers, guide pilot projects, and ensure successful deployments, collaborating mostly remotely with occasional on-site workshops. Monitor system performance and reliability, add to logging, billing and authentication services, and build internal tooling to automate repetitive tasks. Provide feedback on patterns, pain points, and reusable modules to the core product team to influence the future direction of the AI platform.

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As an AI Deployment Engineer, you will serve as the primary technical subject matter expert post-sale for a portfolio of customers, embedding deeply with them to design and deploy Generative AI (GenAI) solutions. You will engage with senior business and technical stakeholders to identify, prioritize, and validate the highest-value GenAI applications in their roadmap, and accelerate customer time to value by providing architectural guidance, building hands-on prototypes, and advising on best practices for scaling solutions in production. You will maintain strong relationships with leadership and technical teams to drive adoption, expansion, and successful outcomes. Additionally, you will contribute to open-source resources and enterprise-facing technical documentation to scale best practices across customers, share learnings and collaborate with internal teams to inform product development and improve customer outcomes, and codify knowledge and operationalize technical success practices to help the Solutions Architecture team scale impact across industries and customer types.

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The Deployment Architect is responsible for partnering directly with healthcare clients to understand their operational workflows and translate their technical requirements into AI-powered conversational solutions. They spend multiple days onsite weekly at customer locations to work alongside clinical, operational, and IT leaders to implement, operationalize, and scale Hippocratic AI's solutions. Responsibilities include defining, documenting, and driving the technical architecture to integrate with client EHR systems, CRMs, population health tools, and other platforms; designing, customizing, and deploying scalable AI agents for customers; leading the technical post-sale implementation process as the primary technical contact; collaborating cross-functionally with engineering, product, machine learning, clinical, and sales teams to meet customer needs; and developing reusable tools, playbooks, and frameworks to improve the scalability and efficiency of implementations. The role requires physical presence at client sites in Charlotte, NC weekly, plus occasional travel to Hippocratic AI offices for strategic planning and team sessions.

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As a Forward Deployed Engineer at Dust, your responsibilities include writing production-quality code to build custom integrations, APIs, and tooling for enterprise customers where off-the-shelf solutions are insufficient. You will contribute features and improvements directly to the Dust platform based on customer requirements and field insights. You act as a key cross-functional partner by collaborating with Sales to help onboard customers and with Customer Success to ensure users maximize the value of Dust. You help set the product roadmap by surfacing feedback and insights from customers, partnering with Design and Engineering. You lead demo calls, communicate Dust's value proposition to buyers and evaluators, and act as a trusted advisor to strategic customers by helping set up their Dust workspace, data connections, AI assistants, and workflows. You identify and highlight successful use cases and craft content to help users maximize Dust's value. Additionally, you lead workshops and training sessions to demonstrate advanced features and facilitate customer access to advanced use-cases through Dust's Developer platform and API.

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As an AI Solution Architect at Mistral AI, the responsibilities include driving the adoption and deployment of Mistral's AI solutions by working closely with customers from strategic vision to production implementation. This involves leading executive-level workshops to identify business challenges and opportunities, co-creating AI adoption roadmaps with customers, and collaborating with Account Executives to develop business cases and align solutions with customer objectives. The role requires architecting end-to-end AI solutions that integrate Mistral's models and platform into customer workflows and infrastructure, partnering with the Applied AI team to design, prototype, and deploy solutions, and overseeing pilot projects and proofs-of-value to demonstrate technological potential. The architect serves as a trusted advisor guiding customers' AI strategies, monitoring KPIs related to business outcomes, and identifying expansion opportunities. Additionally, the role acts as a liaison between customers and internal teams, develops reusable assets and best practices for consistent delivery, and involves travel to foster client relationships and support on-site deployment.

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Serve as the primary technical subject matter expert on OpenAI Codex for a portfolio of customers, embedding deeply with them to enable their engineering teams and build coding workflows. Partner directly with customers to design and implement AI-enhanced development workflows, from rapid prototyping through scalable production rollout. Build high-quality demos, reference implementations, and workflow automations, using Codex itself as part of your development process. Lead large-format workshops, technical deep dives, and hands-on enablement sessions to help engineering organizations adopt AI coding tools effectively and safely. Contribute technical content including examples, guides, patterns, and best practices to the OpenAI Cookbook to assist the broader developer community with Codex. Gather high-fidelity product insights from real customer deployments and translate them into clear product proposals and model feedback for internal teams. Influence customer strategy and decision-making by framing how AI coding tools fit into their SDLC, technical roadmap, and organizational workflows. Serve as a trusted advisor on solution architecture, operational readiness, model configuration, security considerations, and best-practice adoption.

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The Solutions Engineer (AI/ML, Pre-Sales) will work closely with strategic customers to understand their data curation needs, business challenges, and technical requirements. The role involves leading end-to-end customer proofs of concept (PoCs) that connect data curation to training behavior and evaluation outcomes, including dataset analysis, training plan design, and interpreting results. They will partner with customer machine learning teams to map data and curation strategies, design and execute evaluation plans for base and post-trained models, select appropriate benchmarks and metrics, and run model evaluations. Additionally, the engineer will produce customer-ready evaluation reports detailing methodology, metrics, baselines, ablations (e.g., curated vs raw data), conclusions, and recommendations for productionization. They must communicate technical results effectively to both ML experts and executive stakeholders, explaining tradeoffs in compute, latency, and deployment cost. Collaboration with go-to-market, engineering, and research teams is essential to deliver compelling demos, align on requirements, and incorporate customer insights into model training and product strategies. The role also includes providing technical guidance, training, and documentation to enable prospects to confidently assess the solution.