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Principal Solutions Architect, AI Ecosystem & Alliances

Wekatest

U.S. Remote (United States) Remote permanent

Posted: March 27, 2026

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Quick Summary

We are seeking a technically fluent Principal Solutions Architect to lead our strategic partnership strategy across the enterprise AI infrastructure ecosystem.

Job Description

About the Role

We are seeking a technically fluent Principal Solutions Architect to lead our strategic partnership strategy across the enterprise AI infrastructure ecosystem. You will define joint value propositions that articulate the combined strength of our technology alongside partner platforms, creating differentiated solutions across the full AI stack.

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.

Key Responsibilities

Partnership Strategy & Alliance Management


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.

Qualifications

Required


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.

Preferred


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.

The WEKA Way:

• 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.

Concerned that you don’t meet every qualification above?

Studies have shown that women and people of color may be less likely to apply for jobs if they don’t meet every qualification specified. At WEKA, we are committed to building a diverse, inclusive and authentic workplace. If you are excited about this position but are concerned that your past work experience doesn’t match up perfectly with the job description, we encourage you to apply anyway – you may be just the right candidate for this or other roles at WEKA.

WEKA is an equal opportunity employer that prohibits discrimination and harassment of any kind. We provide equal opportunities to all employees and applicants for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

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