Outcomes Architect (Remote - North Amer

Docket; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Docket is seeking an experienced Outcomes Architect to ensure customers achieve measurable pipeline, value, and ROI. You will own customer journeys end-to-end, from pilot to renewal, and drive strategic outcomes through AI-driven marketing capabilities.

You will design and tune agent prompts, integrate with major platforms, and translate data into actionable guidance for CMOs and demand-gen leaders, while growing the account with new use cases and deeper product feedback.

Qualifications

• 4+ years in B2B marketing, demand gen, growth or marketing ops
• Proven track record owning pipeline, MQL or conversion targets
• AI-native with real process-building experience using AI
• Hands-on experience with conversational AI and prompts design
• Experience at AI-native or early-stage SaaS company and with US customers

Responsibilities

• Own 15–25 annual customers from pilot live through renewal and expansion.
• Define success, set baselines, measure pipeline, value and ROI for customers.
• Design and tune AI agents: prompts, routing rules and agent behavior.
• Integrate agents with HubSpot, Salesforce, Gong, webhooks and APIs; trace lead flows.
• Analyze conversation data to identify conversion signals and leakage.
• Provide clear recommendations to CMOs and demand-gen leaders; drive action.
• Identify next agents or use cases to grow accounts and build business cases.
• Convey customer feedback to Product with evidence to shape the product.
• Develop workflows and automations to manage a full portfolio of accounts.

Skills

B2B marketing

Demand generation

Growth strategy

Marketing operations

AI-native

Prompt engineering

Education

Bachelor's degree in Marketing or related field

Tools

HubSpot workflows

Clay tables

Zapier / Zaps

Job description

About Docket

Docket is the AI Marketing Agent platform helping B2B marketing teams move past the broken MQL model. Our agents engage buyers in real conversations, qualify intent using our proprietary Sales Knowledge Lake™, and surface Agent Qualified Leads (AQLs), a far better signal than form fills and lead scores.

We're building the category of agentic marketing. We need an Outcomes Architect to make sure every customer gets measurable pipeline, value and ROI from it.

Why this role exists

AI agents don't need adoption. Nobody has to be trained to log in, so the traditional CSM job of driving usage doesn't apply here.

What our customers need is a strategic partner. Someone who understands their business, their role and the problems they're trying to solve. Someone who helps them decide which outcomes matter, measures them, changes the approach when the numbers fall short, and knows where to double down when they work.

That's an Outcomes Architect. The role is closer to strategy consulting than account management, with real technical depth underneath. You'll own customers from pilot kickoff through renewal and expansion, and you'll be measured on the results they get.

What You'll Own

• Your customers, end to end. Typically 15–25 annual customers. You take over once the agent is live and stay with the account through renewal and expansion, so each customer has one owner.
• The outcome, not the relationship. You define success with the customer, set the baseline, measure it, and own the results: pipeline, value and ROI.
• Retention and growth. Renewals, expansion into new agents and use cases, and customer stories we can share.

What You'll Do

• Set the bar for the year. Build on the results each customer has already seen, agree the year's goals and baseline with them, and deliver the business outcomes they bought Docket for, through renewal and expansion.
• Design and tune the agents. Prompts, qualification logic, routing rules and agent behavior.
• Connect the stack. Integrate agents with HubSpot, Salesforce, Clay, Gong, webhooks and APIs, and trace where leads get lost.
• Find the signal. Analyze conversation and visitor data to see what's converting, what's leaking and what the market is asking about.
• Drive the decision. Turn analysis into clear recommendations for CMOs and demand gen leaders, and walk them through what to change.
• Grow the account. Spot the next agent or use case each customer needs, and build the business case for it.
• Shape the product. Bring customer feedback to Product with evidence, not anecdotes.
• Run on AI yourself. Build the workflows, prompts and automations that let you manage a full portfolio without drowning in it.

Who You Are

• You've been the customer. 4+ years in B2B marketing, demand gen, growth or marketing ops. You've owned pipeline, MQL or conversion targets, and you know what a CMO is measured on. A traditional CSM background isn't what we're looking for.
• You own numbers. You can name a metric you were accountable for, where it started, where you took it, and what you changed.
• You're AI-native, not just AI-comfortable. You've rebuilt a real process with AI, not just used it to write faster, and you can show us what you built.
• You've built with conversational AI. Hands-on prompt engineering or conversational AI work, not just reading about it.
• You're technical without an engineering title. You've built Zaps, Clay tables, HubSpot workflows or prompt chains because it was faster than filing a ticket.
• You've worked at an AI-native or early-stage SaaS company. You know how to move fast when the playbook is still being written.
• You've worked with US customers. You're comfortable running calls and building relationships with US-based marketing and revenue leaders.
• You tell executives the truth. You can tell a CMO their agent isn't converting, back it with data, and come with a plan.
• You thrive when the goal isn't fully defined. You can work out what success looks like with a customer after kickoff, then go deliver it.

Nice to have

• Experience selling or implementing marketing automation or martech

How We Interview

Come ready to show something real you built with AI: a prompt, an agent, a workflow or an automation. Walk us through the problem it solves, how you built it, what broke along the way, and how you know it works. No-code builds are welcome. An engineering background isn't required.