AI Platform Solutions Architect

As an AI Platform Solutions Architect, you will be the bridge between customers, product, engineering, and sales. You will determine how customer requirements can be addressed through platform configuration, enterprise context modeling, AI agent orchestration, integrations, and workflows. You will also play an important role in influencing the future of the platform by identifying product improvements, new capabilities, and opportunities.

Approximately 20% of your time will support enterprise sales by leading technical discovery, product demonstrations, and architecture discussions.

You will partner directly with the Founder & CEO on strategic customers, product roadmap, solution architecture, and go-to-market initiatives. This is a highly visible role with significant ownership and influence over both customer success and product direction.

Customer Engagement & Solution Architecture

• Partner with enterprise stakeholders to understand business objectives, decision workflows, and success criteria.
• Lead technical implementation and validate solution performance, accuracy, and business outcomes.
• Configure and optimize platform capabilities, including data integrations, semantic context, knowledge models, AI agents, workflows, and business context for customer-specific use cases.
• Identify platform gaps and collaborate with Product and Engineering to improve platform capabilities.
• Ensure successful customer onboarding, adoption, and business outcomes.
• Help customers maximize long-term platform value.
• Serve as the technical bridge between Customers, Product, Engineering, Customer Success, and Sales.

Sales Engineering (Approximately 20%)

• Respond to technical architecture discussions, RFPs, and security questionnaires.
• Lead technical discovery during enterprise sales engagements.
• Support strategic customer engagements, technical workshops, and product demonstrations.
• Act as the trusted technical advisor throughout the sales cycle.

Required Qualifications

• 6+ years of experience in Solutions Engineering, Solutions Architecture, Enterprise Architecture, Technical Consulting, or similar customer-facing technical roles.
• 3+ years of hands-on experience building and deploying production-grade AI/ML applications, including LLM-powered Agentic solutions.
• Experience implementing or architecting enterprise AI, SaaS, data, analytics, or automation platforms.
• Strong experience with modern AI technologies, including LLMs, Agentic AI, AI Agents, RAG, and prompt engineering.
• Solid understanding of enterprise architecture, APIs, data integration, cloud platforms, and modern data ecosystems.
• Experience translating customer business requirements into scalable technical solutions.
• Strong hands-on experience with Python, SQL, REST APIs, and enterprise system integrations.
• Strong customer-facing communication, presentation, and solution workshop facilitation skills.
• Comfortable working in a fast-moving startup with high ownership, ambiguity, and a builder mindset.

Nice to Have

• Experience with knowledge graphs, semantic technologies, or enterprise metadata.
• Experience with vector databases and AI orchestration frameworks (e.g., LangGraph, LangChain, CrewAI, Semantic Kernel).
• Experience building enterprise AI copilots or agentic workflows.
• Familiarity with BI, analytics, or decision intelligence platforms.