Client Technical Solutions Architect (AI Solutions Deployment) 

 

Role Overview 

The Client Technical Solutions Architect is a strategic, client-facing role responsible for deploying and customizing advanced AI solutions on top of our company’s AI platform. In this hands-on role, you will work closely with clients to understand their business challenges and translate them into effective technical solutions. You will also collaborate internally with product and engineering teams to ensure the AI platform is configured and extended to deliver maximum value for each client. The ideal candidate combines strong technical aptitude with excellent stakeholder management skills, ensuring that complex AI solutions are delivered smoothly and aligned with client objectives across various industries. 

Responsibilities 

• Deploy and Customize AI Solutions: Implement and tailor our platform’s AI capabilities to solve clients’ specific business problems, both on-site at client locations and through remote collaboration. 

• Client Engagement and Requirements Gathering: Work directly with client stakeholders to understand their requirements, pain points, and goals. Translate business needs into technical solutions and actionable project plans, ensuring clarity between client expectations and delivered functionality. 

• Solution Design and Implementation: Design end-to-end workflows and AI solution architectures that integrate with clients’ existing systems. Develop and test custom modules, data pipelines, and prompts on our platform to meet use-case requirements. 

• Internal Collaboration: Partner with internal product managers and engineering teams to refine platform features and capabilities. Provide feedback from field deployments to influence product roadmaps and improve our AI platform’s effectiveness for all clients. 

• Project Management and Delivery: Oversee the deployment lifecycle from proof-of-concept to production rollout at client sites. Ensure solutions are delivered on time and meet quality standards, while managing technical issues or risks proactively. 

• Stakeholder Management: Manage relationships with client technical teams and business leaders. Communicate progress, present solution demos, and adjust plans based on stakeholder feedback. Act as a trusted technical advisor, aligning the AI solution with the client’s strategic objectives and demonstrating value. 

• Training and Knowledge Transfer: When needed, provide hands-on training and guidance to client teams on using and maintaining the AI solutions. Document configurations and best practices, enabling clients to become self-sufficient with the deployed technology. 

Requirements 

• Education and Experience: Bachelor’s degree in Computer Science, Engineering, or a related field. 7+ years of experience in software engineering, data engineering, or a similar technical role that involved building or deploying software solutions. 

• AI Expertise: Practical experience working with AI/ML technologies, especially Natural Language Processing. Familiarity with prompt engineering techniques and working with large language models or conversational AI systems is highly desirable. 

• Technical Proficiency: Strong programming and scripting skills (e.g., Python, Java, or similar) to customize solutions and integrate systems. Experience with APIs, data pipelines, and cloud platforms or ML frameworks for deploying AI solutions. 

• Solution Architecture Skills: Ability to design system architectures and workflows that are scalable, secure, and maintainable. Experience integrating AI solutions into existing enterprise environments (data sources, databases, APIs, etc.). 

• Problem-Solving: Proven ability to troubleshoot technical issues and optimize AI models or pipelines. A creative mindset to adapt and tailor solutions to unique client scenarios, with a focus on delivering business value. 

• Communication and Stakeholder Management: Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders. Experience gathering requirements and maintaining client relationships in a professional services or customer-facing capacity. 

• Team Collaboration: Comfortable working in cross-functional teams and fast-paced environments. Able to coordinate between client personnel and internal teams, balancing priorities and ensuring alignment on solution delivery. 

Preferred Qualifications 

• Advanced Education: Master’s degree in Computer Science, Data Science, or related field with a focus on AI/ML is a plus. 

• Industry Experience: Experience in a client-facing technical role (e.g. solutions architect, forward-deployed engineer, or technical consultant) where you implemented enterprise software or AI solutions for clients. Exposure to multiple industries or use cases is advantageous. 

• ML Tools: Familiarity with AI libraries and ML tools (such as TensorFlow, PyTorch, Hugging Face, or similar frameworks) and experience fine-tuning language models or building chatbots. Knowledge of prompt engineering best practices for LLMs is a strong plus. 

• Cloud and Data: Experience with cloud services (AWS, Azure, or Google Cloud) especially their AI/ML offerings, and understanding of data engineering workflows (ETL processes, data lakes, etc.). Certifications in cloud architecture or data science can be beneficial. 

• Project Leadership: Demonstrated experience leading technical projects or deployments, including coordinating with multiple stakeholders. Any experience in change management or user training during technology rollouts is a plus. 

 

Attributes 

• Empathy & Ownership: You listen carefully to user needs and take full ownership of delivering great experiences. 

• Startup Mentality: You move fast, learn quickly, and are comfortable wearing many hats. 

• Detail-Oriented: You care about the little things  

• Mission-Driven: You want to solve important, high-impact problems that matter to real people. 

• Team-Oriented: Low ego, collaborative, and excited to build alongside highly capable engineers, designers, and domain experts. 

 

Travel 

This position requires the ability to travel to client sites as needed for on-site deployments and collaboration. Travel is estimated at approximately 20–30% of the time (varying by project), and flexibility is expected to accommodate key client engagement activities.