Principal AI Solutions Engineer

Job Description:

DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business — today and in the future. 

The Pre-Sales Principle AI Solutions Engineer plays a pivotal role in helping enterprise customers see, feel, and believe in the value of agentic AI and ML platforms. Sitting at the intersection of business strategy, AI application design, and polished execution, your primary mission is to rapidly build enterprise-grade MVP agentic AI applications. You will partner with prospective customers and sales teams to map loosely defined problems into compelling, production‑inspired prototypes. These MVPs serve as credible, extensible foundations that showcase technical depth and accelerate time-to-value, acting as the bridge between immediate problem-solving and long-term platform adoption.

Key Responsibilities

Business-to-Technical Translation & Problem Understanding

• Partner with Sales Teams: Understand customer missions, strategic priorities, and constraints through short discovery sessions.

• Map Capabilities: Translate business needs into platform capabilities, tailoring messaging for different personas (CIO, CTO, Chief Data Officer, program leads, technical practitioners).

• Identify Value: Pinpoint high-leverage automation and decision points where agentic AI can create immediate, visible value, translating ambiguous problems into clear user journeys and agent responsibilities.

Agentic AI Solution Design & Prototyping

• Rapid MVP Build: Design and implement end-to-end agentic AI MVPs, including multi-agent orchestration, tool use, memory, Model Context Protocol (MCP) servers, and agent observability.

• Deployment Readiness: Define key technical requirements, recommend deployment models meeting specific security mandates, and advise on data readiness to ensure quick time-to-value for new and expansion opportunities.

• Frontend & UX: Build intuitive, enterprise‑grade UIs using React and modern design systems (e.g., shadcn/ui) to communicate agent behavior transparently.

• Architectural Soundness: Select and integrate appropriate LLMs, frameworks, and agent architecture to balance speed, cost, and explainability while establishing scalable platform foundations.

Demo Execution & Sales Collaboration

• Outcome-Oriented Demos: Deliver engaging live demos that tell a clear story: problem → agentic solution → business impact. Help shape and refine use cases based on account maturity and strategic alignment.

• Trusted Advisor: Act as a technical pillar across the sales team, supporting Account Executives, Strategic Account Directors, and BDRs with knowledge and assets that advance AI adoption.

• Iterative Refinement: Iterate rapidly based on customer feedback during pilots, workshops, or proofs of value (POVs).

Cross-Functional Feedback & Compliance Alignment

• Security & Governance: Support conversations around AI governance, data security, model transparency, and responsible AI practices in alignment with regulations.

• Internal Feedback Loop: Provide structured feedback on customer needs, procurement hurdles, and architectural gaps to Product, Marketing, and Enablement teams to keep offerings relevant.

• Reusable Assets: Contribute reusable patterns, templates, and internal best practices to accelerate future MVP delivery and platform selling.

Knowledge, Skills, and Abilities

Pre-Sales & Platform Selling Experience

• Demonstrated success supporting sales pursuits (new logos and account expansion) with deep technical expertise and solution design.

• Strong ability to translate agentic AI and ML platform capabilities into compelling value propositions.

• Prior experience turning rapid MVPs into production applications or long‑term enterprise platforms.

Core Technical Skills

• Hands-on experience building agentic AI applications using modern LLM frameworks, orchestration patterns, and backend engineering (Python, TypeScript