AI Outcomes Manager

At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries.

About the role

The AI Outcomes Manager is DevRev's unified post-sales owner — bringing Customer Success and Customer Support together into a single role. Instead of handoffs between siloed teams, you own accounts end-to end: resolving issues, driving adoption, managing escalations, and making sure customers extract measurable value from what they bought.

You manage each account by its health and needs — proactively spotting risk and opportunity — rather than by whether a given interaction is labelled "support" or "success."

AI is your multiplier, not a tool you use on the side. Our AI agent handles first-line triage, ticket classification, routing, knowledge retrieval, and deflection — so you can focus on what AI can't do: complex judgment, strategic enablement, relationship building, and driving outcomes. You'll be measured not just by what you do directly, but by how well you leverage AI to scale across a full portfolio.

What you'll own

Your portfolio — a book of enterprise and growth accounts under single, accountable ownership. The model protects depth over volume.

The customer relationship, end-to-end

• Own accounts from implementation and go-live through adoption, renewal health, and expansion.
• Be the customer's single point of trust — no handoffs, in good times and bad.
• Stay accountable for the outcome even when another team is responsible for the underlying work ("more accountability, less responsibility").

Implementation & go-live

• Align on scope, success criteria, and the value the customer is buying before kickoff. DevRev · Customer Experience — Customer Outcomes 1
• Validate what was sold against what's feasible; close gaps and secure sign-off.
• Own go/no-go readiness — flag risk and hold the line when a launch isn't ready.

Ticket lifecycle, powered by AI

• Respond within SLA — AI drafts, you review and personalize.
• Validate and correct AI's classification and severity; your corrections train the model.
• Own tickets through resolution; decide workaround vs. code fix and route to engineering while staying the owner.

Adoption & value

• Track usage trends and flag drops early using AI anomaly signals; turn them into proactive outreach.
• Run enablement sessions; compare entitlements to actual usage and close adoption gaps.
• Translate usage into business value (time saved, cost avoided, deflection); build the roadmap into every business review.

Relationship & commercial

• Keep relationships multi-threaded and engage executive sponsors.
• Act on account signals before the customer raises a problem.
• Run renewal reviews ahead of expiry; source and flag expansion opportunities to Sales.

Who we're looking for

• Technically oriented and AI-capable — comfortable with APIs, tracing issues, and explaining root causes to both engineers and customers.
• An owner — you can carry a large B2B portfolio end-to-end, from ticket resolution through business reviews.
• A strong communicator — you run customer calls confidently and write clear RCA reports and QBR materials.
• AI-native — you embrace AI as your operating layer, actively train the model, and measure your own leverage.
• Commercially aware — you understand ACV, track utilization, spot expansion signals, and connect usage to renewal confidence.
• Comfortable with ambiguity — this is a new operating model; you'll help shape it, not just follow playbooks.
• Deep in at least one domain — with the ability to cross-train and advise.

Qualifications

• Minimum a B.Tech (or equivalent bachelor's degree in engineering / technology), or a postgraduate degree in management (MBA or equivalent).
• 3+ years in customer-facing technical roles (support engineering, solutions engineering, CSM, or TAM).
• Hands-on with at least one of: ticketing systems, CRM, workflow automation, analytics platforms, or developer tools.
• Background in fintech, enterprise SaaS, or high-volume support environments preferred.
• Experience across both support and success motions is highly valued.

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