What are the responsibilities and job description for the GenAI Technical Solutions Architect position at ClifyX?
Position Title: GenAI Technical Solutions Architect
Location: Cupertino/Sunnyvale, CA (Hybrid)
Duration: 12 Months
What You''ll Do
- Build & Prototype
- Assemble AI-powered workflows using existing enterprise tools, MCPs, and APIs
- Write scripts, automations, and glue code to connect systems and fill gaps
- Prototype rapidly — get a working version in front of users fast, then iterate
Evaluate & Advise
- Assess technical feasibility of proposed AI use cases — what''s possible with existing tools, what needs IS&T involvement
- Evaluate new tools and capabilities as they become available — is it relevant, is it approved, how does it fit?
- Know when to build vs. when to escalate to IS&T for platform-level support
Integrate & Scale
- Turn one-off prompt solutions into reusable, maintained tools
- Build and maintain the process repository as a living product
- Configure and connect AI solutions to existing BPR and Sales systems
- Ensure solutions are reliable and handle edge cases - Stay current on the enterprise AI landscape — what IS&T ships, what MCPs are available, what''s newly approved
Key Qualifications
- 5 years in a technical role — solutions engineering, technical consulting, or systems integration
- Strong understanding of full-stack architecture — frontend, backend, APIs, databases. You know how applications are structured and how the pieces connect.
- Proficient with React, TypeScript, Python, and/or Node.js — you can read, debug, and modify code confidently
- Effective AI-native builder — you use LLMs (Claude, Copilot, etc.) to write code, and you know how to prompt, evaluate output, and iterate until it''s right
- Experience integrating with LLMs/AI in applications — API calls, handling responses, building AI-powered features
- UX sensibility — you build things that look and feel good, not just things that work
- Self-directed problem solver — given an unfamiliar infrastructure, you figure it out
- Strong understanding of APIs, data flows, and how enterprise systems connect
- Able to navigate and leverage existing platforms — MCPs, enterprise AI tools, internal tooling — without needing to build them from scratch
- Can translate between technical and business audiences
- Strong prototyping mindset — ship fast, iterate, don''t over-engineer
- Self-directed and comfortable with ambiguity
Preferred
- Experience assembling solutions in large enterprise environments with existing tool ecosystems
- Familiarity with data analysis tools (SQL, DuckDB, pandas) for workflow automation
- Background in Sales Operations, CRM, or enterprise business systems