TechTorch
AI Architect/AI Subject Matter Expert
United States
Sponsorship not specifiedDetected 13 hours ago
FastAPIGitVector DatabasesAWSAzureCI/CDLLMsRAGAgentic AILangGraphA/B TestingStakeholder ManagementLeadershipCommunicationCollaboration
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Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- This is a client-facing consulting role combining AI strategy, enterprise architecture, deep technical expertise, and thought leadership.
- You will help shape both client AI roadmaps and TechTorch's AI offerings.
Responsibilities
- Lead AI strategy, discovery workshops, and executive advisory sessions.
- Design enterprise AI architectures and implementation roadmaps.
- Partner with engineering teams to guide implementation and review solution designs.
- Support proposals, pre-sales, and executive presentations.
- Client First - We focus relentlessly on delivering outcomes that create value for our clients
- We, Not Me - We win together. Collaboration drives transformation at scale
- Own It - We take accountability for results, delivering on what we promise
Requirements
- 8+ years in AI, enterprise architecture, solution architecture, or software engineering.
- Proven experience designing production AI solutions.
- Experience leading AI discovery workshops and roadmap definition.
- Ability to translate business challenges into scalable AI solutions.
- Technical Expertise
Skills
- AI Architect / AI Subject Matter Expert
- About TechTorch
- About the AI Practice
- The AI Practice helps organizations move beyond AI experimentation into production.
Compensation
- Semi-annual team off-sites - we come together in person at least twice a year to connect, recharge, and do the work that's better face-to-face.
Benefits
- Flexible, remote-first work environment with high-performance expectations and autonomy.
Company info
- We are looking for a AI Architect / AI Subject Matter Expert to lead strategic AI engagements for enterprise clients.
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This listing is sourced directly from TechTorch's careers page and normalized into a canonical job model.