Principal Solutions Architect, AI Ecosystem & Alliances

This role sits at the intersection of partnership strategy, technical architecture, and field enablement. You will be responsible for shaping long-term alliance roadmaps, engaging credibly with solution architects, and preparing global GTM teams to effectively position joint solutions., * Ecosystem Leadership: Lead alliance strategy across cloud providers, silicon vendors, MLOps platforms, enterprise Linux/container platforms, and vector database providers.

• Joint Business Planning: Build structured business plans with shared objectives, integration milestones, and multi-year roadmaps.
• Executive Relationships: Cultivate relationships from C-suite sponsors to technical architects to maintain long-term strategic alignment.
• Market Assessment: Continuously identify new integration opportunities and negotiate partnership frameworks in collaboration with Legal and BizDev.

Joint Solution Development & Architecture

• Full-Stack Architecture: Define architectures spanning data ingestion, feature engineering, model training, fine-tuning, and inference serving.
• Technical Integration: Drive certified workstreams across priority areas:
• Enterprise Linux & Containers: Certified integrations with platforms like OpenShift to ensure AI workloads are deployable in hardened environments.
• Orchestration: Develop validated deployment architectures with Kubernetes optimized for AI workloads.
• Vector Databases: Build integrations for semantic search and Retrieval-Augmented Generation (RAG) workflows.
• Engineering Liaison: Coordinate cross-organizational technical resources to produce reference architectures, validated blueprints, and technical PoCs.
• Product Influence: Stay current on inference optimization and retrieval architectures to ensure partner APIs/SDKs are prioritized in the internal product roadmap.

GTM Enablement & Thought Leadership

• Field Readiness: Develop technical battlecards, solution briefs, and demo environments to equip partner and internal sales teams.
• Technical Training: Design and deliver enablement programs for solution engineers to ensure they can confidently deploy joint AI solutions.
• Voice of the Partner: Feed market intelligence and integration feedback back into internal product strategy.
• Industry Presence: Represent the company at conferences and summits; author whitepapers and technical blogs on integrated AI infrastructure., * We are Accountable: We take full ownership, always-even when things don’t go as planned. We lead with integrity, show up with responsibility & ownership, and hold ourselves and each other to the highest standards.
• We are Brave: We question the status quo, push boundaries, and take smart risks when needed. We welcome challenges and embrace debates as opportunities for growth, turning courage into fuel for innovation.
• We are Collaborative: True collaboration isn’t only about working together. It’s about lifting one another up to succeed collectively. We are team-oriented and communicate with empathy and respect. We challenge each other and conduct positive conflict resolution. We are being transparent about our goals and results. And together, we’re unstoppable.
• We are Customer Centric: Our customers are at the heart of everything we do. We actively listen and prioritize the success of our customers, and every decision we make is driven by how we can better serve, support, and empower them to succeed. When our customers win, we win.

• 8+ years of experience in alliance management, partner engineering, or technical strategy within enterprise software, cloud, or AI/ML platforms.
• Strong Technical Foundation: Familiarity with LLM deployment stacks, GPU compute, and ML frameworks (PyTorch, TensorFlow, JAX).
• AI Lifecycle Expertise: Experience across the software stack, including fine-tuning, inference serving, and MLOps monitoring.
• Solution Articulation: Proven ability to translate complex technical depth into clear, compelling narratives for both executive and technical audiences.
• Execution: Demonstrated success in executing technology partnerships that result in measurable market impact and revenue growth., * Cloud-Native Proficiency: Deep experience with OpenShift, Rancher, or Tanzu and Kubernetes-native deployment patterns.
• Modern Data Stack: Familiarity with purpose-built vector stores and their role in RAG architectures.
• Ecosystem Knowledge: Experience with hyperscalers, GPU vendors, and data lakehouse providers.
• Advanced Education: MS/PhD in Computer Science or an MBA is highly desired.
• Community: Involvement with open-source AI communities or standards bodies.