Gen AI Technical Solutions Architect
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
+1 more
Job description
To build and scale AI-powered solutions, You turn designed workflows into working solutions leveraging existing enterprise tools, MCPs, APIs, and AI platforms to assemble and configure what the team needs. You code when
needed, but your primary value is knowing what’s available and wiring it together effectively.
What You’ll Do
Build & Prototype
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Assemble AI-powered workflows using existing enterprise tools, MCPs, and APIs
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Write scripts, automations, and glue code to connect systems and fill gaps
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Prototype rapidly get a working version in front of users fast, then iterate
Evaluate & Advise
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Assess technical feasibility of proposed AI use cases what’s possible with existing tools, what needs IS&T involvement
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Evaluate new tools and capabilities as they become available is it relevant, is it approved, how does it fit?
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Know when to build vs. when to escalate to IS&T for platform-level support
Integrate & Scale
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Turn one-off prompt solutions into reusable, maintained tools
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Build and maintain the process repository as a living product
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Configure and connect AI solutions to existing BPR and Sales systems
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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
Requirements
5+ years in a technical role solutions engineering, technical consulting, or systems integration
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Proficient in Python and/or TypeScript can write scripts, automations, and integration code
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Hands-on experience with LLMs and AI tools (Claude, ChatGPT, etc.) prompting, API usage, building AI-powered workflows
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Strong understanding of APIs, data flows, and how enterprise systems connect
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Able to navigate and leverage existing platforms MCPs, enterprise AI tools, internal tooling without needing to build them from scratch
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Can translate between technical and business audiences
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Strong prototyping mindset ship fast, iterate, don’t over-engineer
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Self-directed and comfortable with ambiguity
Preferred
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Experience assembling solutions in large enterprise environments with existing tool ecosystems
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Familiarity with data analysis tools (SQL, DuckDB, pandas) for workflow automation
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Background in Sales Operations, CRM, or enterprise business systems
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