AI Solutions Architect Jobs

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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 AI Deployment Engineer serves as the primary technical subject matter expert post-sale for a portfolio of customers, embedding deeply with them to design and deploy Generative AI solutions. They engage with senior business and technical stakeholders to identify, prioritize, and validate the highest-value GenAI applications in customers' roadmaps. The role accelerates customer time to value by providing architectural guidance, building hands-on prototypes, and advising on best practices for scaling solutions in production. The engineer maintains strong relationships with leadership and technical teams to drive adoption, expansion, and successful outcomes. They contribute to open-source resources and enterprise-facing technical documentation to scale best practices across customers. The engineer shares learnings and collaborates with internal teams to inform product development and improve customer outcomes. Additionally, they codify knowledge and operationalize technical success practices to help the Solutions Architecture team scale impact across industries and customer types.

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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 high-value GenAI applications in their roadmap. Your role includes accelerating 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, collaborate with internal teams to inform product development and improve customer outcomes, and codify knowledge to help the Solutions Architecture team scale impact across industries and customer types.

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The AI Deployment Engineer is responsible for serving as the primary technical subject matter expert post-sale for a portfolio of customers, embedding deeply with them to design and deploy Generative AI solutions. They engage with senior business and technical stakeholders to identify, prioritize, and validate high-value GenAI applications in the customers' roadmaps. The role involves accelerating customer time to value by providing architectural guidance, building hands-on prototypes, and advising on best practices for scaling solutions in production. The engineer maintains strong relationships with leadership and technical teams to drive adoption, expansion, and successful outcomes. They contribute to open-source resources and enterprise-facing technical documentation to scale best practices, share learnings, and collaborate with internal teams to inform product development and improve customer outcomes. Additionally, they 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 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.

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As a Solutions Architect at Cohere, you will develop and deliver cutting-edge agentic AI solutions using Cohere’s foundation models and Agentic AI Foundry - North. You will architect scalable, secure, and customizable NLP and generative AI solutions tailored to enterprise customer needs. You will collaborate with customers to understand complex workflows, design pilots, and translate business requirements into technical solutions including model fine-tuning, custom agents, and agent orchestration. You will support the deployment and integration of large language models and custom solutions into production environments using Kubernetes, Docker, and cloud infrastructures, ensuring high performance and security. You will lead technical engagements such as deep dives into AI architectures, facilitate workshops, and establish best practices for agent-based AI systems and model customization. Additionally, you will work with product development to provide customer feedback on agentic AI capabilities, contribute to product enhancements, and help shape future features. You will serve as the technical relationship owner, owning the customer narrative, acting as the voice of the customer, and liaising between customers and the product team, providing guidance on best practices for using Cohere, identifying platform improvement areas, and cultivating technical champions within customer organizations to drive adoption and gather feedback to enhance products.

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The Solution Architect is responsible for developing detailed and scalable architectural designs to address client needs using Articul8 products and third-party libraries and tools. They run pilot programs with customers to demonstrate the feasibility and advantages of proposed solutions, including introducing new product features or building prototypes. The role requires working closely with clients to understand business challenges and technical requirements through workshops, meetings, and presentations. They optimize solutions for performance, reliability, and cost-effectiveness, selecting appropriate instance types, auto-scaling configurations, and storage options. Ensuring solutions comply with security best practices and regulatory requirements is necessary, including implementing identity and access management, data encryption, and other security measures. The architect also creates comprehensive documentation and provides training on solution implementation and management. Collaboration with cross-functional teams such as Applied Research, Engineering, Quality Assurance, and Customer Success is required to incorporate innovation and maintain product leadership. Additionally, the role involves mentoring and guiding junior team members and helping to build a culture of rapid innovation.

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The Senior Solution Architect will guide customers through their entire AI journey from initial solution architecture and technical discovery in pre-sales to hands-on implementation and optimization post-sale. Responsibilities include deeply understanding customer business challenges and crafting AI prototypes on the Articul8 platform to address business objectives, leading technical workshops, hackathons, and training sessions to enable customers, collaborating with Sales, Product, and Engineering teams to position the platform and deliver solutions, overseeing installation, configuration, and scaling of the platform in customer environments with a focus on security, reliability, and performance, developing and implementing tailored workflow solutions, architecting and tuning Kubernetes-based environments on AWS, Azure, GCP, and on-premises, delivering enablement workshops and documentation for long-term customer autonomy, monitoring and refining deployments for cost-effectiveness, scalability, and resilience, and gathering customer feedback to influence product roadmap and enhancements.

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Design and deploy scalable architectures for manufacturing use cases including industrial operations such as SCADA/HMI, EDA, IoT, Machine Learning, AI, and advanced analytics. Lead technical workshops, prototype solutions, and oversee platform deployment and optimization. Collaborate with product and engineering teams to incorporate customer feedback into the product roadmap. Advise customers on Articul8 product adoption strategies focusing on differentiating capability, security, cost, and operational efficiency. Architect and tune Kubernetes-based and containerized infrastructure leveraging cloud platforms (AWS, Azure, GCP, or on-premises) to ensure infrastructure excellence. Develop reusable solution templates and document best practices. Partner with sales and business development to drive cloud adoption and align solutions with industry trends. Continuously monitor and improve deployed solutions for performance and scalability. Communicate technical concepts clearly to diverse audiences and advocate for customer needs internally. Stay current with emerging manufacturing and cloud technologies to inform strategy and support other industry verticals when required.