AI Outcomes Associate
UpSmith builds agentic AI systems that help skilled-trades businesses winby converting more demand into revenue without adding payroll. Our flagship platform, Jenny, deploys autonomous AI agents that engage customers, surface revenue opportunities, and execute end-to-end workflows directly inside systems like ServiceTitan.
We are entering a phase where AI capability alone is no longer the bottleneck. Rather, the bottleneck is product outcomes: deploying agents into messy, real-world environments and making them workreliably, measurably, and at scale.
This role exists to own that problem, and associated outcomes with it.
The RoleThe AI Outcomes Associate sits at the intersection of:
- Applied AI & agent design
- Product judgment & abstraction discipline
- Customer success & real-world deployment
You will be responsible for turning AI capability into customer-visible, revenue-driving outcomes. That means working directly with customers, AI Outcomes managers, and engineers to deploy agents, diagnose failures, refine behavior, and prove impact.
This is not a traditional CSM role.
It is a front-line, ownership-heavy role for someone who wants to see their work running in productioncreating real economic value.
What Youll OwnAI Outcomes & Customer Impact- Own the end-to-end success of AI agent deployments for our customers
- Define, track, and improve leading and lagging indicators of agent success (conversion, bookings, revenue lift, customer trust)
- Diagnose failures across data, prompts, tooling, coordination logic, and customer workflows
- Act as the single accountable owner for Is this workingand why?
- Work hands-on with AI agents in production:
- Prompting and behavior design
- Guardrails, fallbacks, and human-in-the-loop escalation
- Partner with core engineering on deeper system improvements surfaced from the field
- Translate customer reality into clear product insights and roadmap input
- Identify when problems are:
- Agent behavior issues
- Product abstraction issues
- Customer workflow mismatches
- Help decide what not to build by grounding decisions in outcomes, not hypotheticals
- Customers expand usage because the configuration, deployment, and ongoing maintenance/support of AI agents measurably drive revenue at clients
- Agent deployments become faster, more repeatable, and less bespoke
- Product and engineering velocity increases due to high-signal field feedback
- You are trusted internally to own some customer outcomes with minimal oversight
- Mission first. Deliver magic for the builders we serve.
- Speed wins. Execute efficiently with bias to action.
- Be an owner. Raise the bar and take pride in the work.
- Choose greatness. We perform best when we play to our superpowers. We hold a high standard for the bets we make
These are not slogans. This role lives or dies by them.
Why This Role MattersUpSmith is moving from Can we build agents? to Can we deploy agents that win?
This role is where that question gets answeredevery day, with real customers, real revenue, and real accountability.
Requirements
What You Must HaveCore Capabilities- Strong analytical and systems thinking skills
- Comfort working across codebases, tooling, product, and customer conversations
- Ability to operate in ambiguity and make sound judgment calls quickly
- Bias toward action with a high bar for quality
- Working knowledge of:
- LLMs and their failure modes
- Prompt engineering
- SQL and data visualization tools (i.e. Tableau, Retool, Metabase)
- You dont need to build solutions from scratch, but you should have the capability and reasoning to scale and help plan for the future on our current systems
- You take responsibility when things dont work
- You care deeply about real-world impact, not demos
- You are comfortable telling hard truthsto customers and teammates
- Willingness to travel frequently to customer sites
- Comfortable operating in high-growth, high-expectation environments
- Management consulting, product ops, or startup experience
- Strong SQL & data visualization skills
- Prior experience deploying AI or automations into production environments
- Familiarity with skilled trades, home services, or operationally complex businesses
- Working knowledge of APIs, data pipelines, and production constraints
