SkillNet Solutions Inc
AI Solutions Architect
Austin, Travis County · Contract
Sponsorship not specifiedDetected 13 hours ago
AWSGCPAzureMachine LearningLLMsRAGLangGraphAI OrchestrationA/B TestingSalesforceCustomer SupportLeadership
About the role
- You will work closely with our engineering, product, and architecture teams.
- Reviewing our current AI initiatives with the engineering teams -- understanding what is working, identifying consolidation opportunities, and collaborating on a path toward a unified platform
- orchestration, intent classification and routing (including compound/multi-label intents), and how context flows between agents and sessions
Responsibilities
- Some weeks are whiteboarding sessions and design reviews; others are deep dives into our existing systems.
- Working with engineers and product leads to design the reference architecture for multi-agent
- Partnering with engineering and product leadership to build a sequenced implementation roadmap that our teams can execute against
- Built both real-time and batch ML pipelines and know when to use which -- streaming inference for live interactions, batch processing for catalog-scale operations, and the infrastructure to support both
- What We Will Build Together
- Over the course of the engagement, you will collaborate with our teams to produce the following artifacts that will guide our platform buildout:
Requirements
- Architected RAG pipelines that went beyond prototyping -- you have dealt with chunking tradeoffs, embedding drift, stale indexes, and retrieval quality at scale
- If you have not done them in production, this is not the right engagement.
Nice to have
- Preferred Skills/Experience:
Skills
- Experience with self-hosted model serving (Ollama, vLLM) for cost optimization or data-sensitive workloads
- Have been the person who wrote the AI platform standards that an engineering org of 50+ adopted
- AI Platform Reference Architecture with decision rationale
- Multi-Agent Orchestration & Context Management Strategy
- Intent Routing Framework with classification taxonomy
- RAG Architecture covering ingestion, retrieval, and serving layers
- Prompt Governance Standards & Tooling Recommendations
- Platform Resiliency & Observability Design
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