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AI Transformation Lead

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Intelliswift - An LTTS Company
Full Time position
Listed on 2026-07-06
Job specializations:
  • IT/Tech
    AI Business & Operations, AI Engineer (Applied/Software), IT Consultant, IT Project Manager
Salary/Wage Range or Industry Benchmark: 120000 - 160000 USD Yearly USD 120000.00 160000.00 YEAR
Job Description & How to Apply Below

Job Title: AI Workflow Architect, Business Operations

Location:
Hybrid - San Jose or San Francisco, CA only

Duration: 6 Months

Work type: W2

Intelliswift Software Inc. conceptualizes, builds, and supports the world's most amazing technology products and solutions. Our team of rich experts from diverse backgrounds contributes to making Intelliswift one of the most reliable partners in IT and Talent solutions. We specialize in delivering world-class Digital Product Engineering, Data Management and Analytics, and Staffing Solutions services to Fortune companies, SMBs, ISVs, and fast-growing startups.

What

You’ll Build:
  • A central knowledge repository that captures structured inputs — test results, PMM project updates, and other recurring information — in a consistent, maintainable format.
  • An AI query layer on top of that repository so any authorized user can ask a question and get an accurate, high-level summary on demand — without needing to coordinate with individual PMMs.
  • The end-state experience: org leadership and teammates can query the tool and provide at least an initial high-level answer immediately, rather than waiting for someone to dig into the data.
  • Lightweight processes and documentation so the team can keep the repository current and the tool useful long after the engagement ends. Secondary objective (stretch, if scope and time allow):
  • Begin establishing easier access to commonly used metrics — reducing the manual coordination, pulling, and reconciliation the team does today — in partnership with Analytics and Finance. The primary deliverable is the knowledge repository; this is a valuable extension if the build progresses ahead of schedule.
What You Need to Succeed
  • An operations mindset:
    You understand how teams function, how information flows, and how to design a tool people will genuinely adopt and maintain — not just a technically impressive artifact. This is a workflow and operations role requiring AI expertise, not a software engineering role.
  • Hands-on fluency with Claude / Glean / Copilot and demonstrably deep expertise with equivalent enterprise platforms and AI agent frameworks. We expect you to be an expert in the tools; you do not need to know client’s internal tooling governance on day one, but you should be able to build with these platforms immediately.
  • A track record of building AI-powered tools — not advising on them. You have personally built and shipped working solutions, whether from scratch or by orchestrating existing AI platforms, LLMs, and agent frameworks.
  • Proven success in introducing user-centric processes:
    Ability to design workflows that others can keep current with minimal friction, including the discipline to make the “keep it updated” step as easy as possible for contributors.
  • Comfort operating with ambiguity and moving fast. A 6-month engagement has no runway for extended ramp-up — you can scope quickly, build, and deliver a working tool within the engagement window.
  • Strong communication skills and the ability to work cross-functionally with marketing, operations, and data partners.
Nice to Have
  • Familiarity working with marketing or PMM organizations.
  • Experience building tools with common enterprise AI platforms and agent tooling.
  • Experience integrating or surfacing data from multiple sources, with an eye toward eventual self-serve metric access.
  • Prior experience working within or alongside a Strategy & Operations function.
Engagement Structure

Month 1 — Scope and design

  • Understand the recurring information needs, define the repository structure and the inputs PMMs will maintain, and confirm the build approach. Ends with an agreed design and build plan.

Month 2-4 — Build.

  • Build the repository and AI query layer. Weekly check-ins with the project lead. Goal: a working tool ready for internal testing by end of month 3.

Month 5-6 — Adopt and hand off.

  • Refine based on real usage, drive adoption with the PMM org, and complete documentation. The tool should be in active use with 2–3 weeks remaining so issues can be resolved while you are still engaged.
Equal Employment Opportunity Statement

Intelliswift celebrates a diverse and inclusive workforce. We offer equal employment…

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