Solutions Architect
Posted 27 Mar 2026
Advertised as “Principal Solutions Architect, AI Ecosystem & Alliances”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 8+ yrs
- Management level
- Individual contributor
- Employment
- Remote
No salary listed for this role.
CertificationsMaster of Business Administration
Field of studyComputer Science
Study levelDoctorate
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
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Ecosystem Leadership: Lead alliance strategy across cloud providers, silicon vendors, MLOps platforms, enterprise Linux/container platforms, and vector database providers.
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Joint Business Planning: Build structured business plans with shared objectives, integration milestones, and multi-year roadmaps.
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Executive Relationships: Cultivate relationships from C-suite sponsors to technical architects to maintain long-term strategic alignment.
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Market Assessment: Continuously identify new integration opportunities and negotiate partnership frameworks in collaboration with Legal and BizDev.
Joint Solution Development & Architecture
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Full-Stack Architecture: Define architectures spanning data ingestion, feature engineering, model training, fine-tuning, and inference serving.
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Technical Integration: Drive certified workstreams across priority areas:
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Enterprise Linux & Containers: Certified integrations with platforms like OpenShift to ensure AI workloads are deployable in hardened environments.
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Orchestration: Develop validated deployment architectures with Kubernetes optimized for AI workloads.
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Vector Databases: Build integrations for semantic search and Retrieval-Augmented Generation (RAG) workflows.
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Engineering Liaison: Coordinate cross-organizational technical resources to produce reference architectures, validated blueprints, and technical PoCs.