Agentic Success Portfolio Lead
San Francisco, CAFull-time$131–207K/yrPosted 2w agoStill listed today
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At a glance
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Job overview
The Agentic Success Portfolio Lead will build and operate the systems, telemetry pipelines, and AI orchestration layer for Atlassian’s Digital Success OS. The role turns customer and product signals into digital journeys, agent plays, and human interventions, partnering across data engineering, analytics, AI, and customer success. It also owns cross-functional execution, journey orchestration, handoffs, and measurement of customer outcomes.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Overview
Working at Atlassian Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. Your Future Team The Digital & Agentic Success team is shaping how we scale customer success through data, automation, and AI-driven orchestration. We are building the systems, intelligence, and operating models needed to turn complex customer signals into proactive, high-impact digital and agentic journeys. We are looking for an Agentic Success Portfolio Lead—a data-forward builder and operator—to lead the systems, telemetry pipelines, and AI orchestration layer that powers our Digital Success OS. In this role, you will bridge data engineering, data science, AI workflows, and customer journey orchestration to support customers at scale with timely digital, agentic, and human interventions.
Responsibilities
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Build Digital Success OS: Create the systems, data flows, and journey orchestration needed to support uncovered accounts, both pilot and scale the pattern across broader customer segments.
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Turn data into action: Convert product telemetry, lifecycle stage, health, contact engagement, sentiment, support, and commercial signals into customer plays, AI-agent triggers, CTAs, and human handoffs.
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Close ownership gaps: Act as the accountable DRI across XFN partners to assess whether systems or process ownership is unclear.
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Protect delivery momentum: Maintain the decision log, architecture principles, dependency map, and change-control process so aligned architecture is not repeatedly reopened without clear rationale.
You will own:
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Data foundation and pipelines: Define requirements for clean, reliable account, contact, product, engagement, lifecycle, and health data. Partner with Data Engineering and RevOps to build durable pipelines, tables, schemas, tagging, and integrations.
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Partnering on Analytics and modeling: Partner with the analytics team on exploratory analysis, segmentation, predictive modeling, and measurement design for adoption, churn, time-to-value risk, expansion readiness, engagement quality, and agent effectiveness.
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AI-agent signal design: Partner with CS AI Agent Engineers, Data Science, AIQ, and Success AI to translate raw metrics and models into practical agent plays, prompts, retrieval logic, escalation rules, and feedback loops.
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Journey orchestration: Operationalize Gainsight Journey Orchestrator, CTAs, shared mailbox workflows, audience rules, consent/contact governance, channel triggers, and journey analytics.
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Digital-to-human handoffs: Define what context moves from digital journeys and AI agents to human teams, and what return signal is needed to continue the journey.
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Measurement and experimentation: Work closely with analytics on cohort analysis, A/B tests, and operating reviews that show impact on adoption, MAU/consumption, engagement, agent invocation, escalation conversion, and prerequisite closure.
Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. This role may also be eligible for benefits, bonuses, commissions, and equity. Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
Pay Ranges
In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are: Zone A: $158,400 - $206,800 Zone B: $142,560 - $186,120 Zone C: $131,472 - $171,644
Qualifications
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Experience with customer success, support, lifecycle, adoption, churn, or consumption analytics in a SaaS environment.
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Ability to partner with Data Science on predictive models, NLP/sentiment analysis, customer behavior models, and real-time orchestration signals.
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Technical fluency with AI-agent workflows, retrieval, prompts, rules engines, model evaluation, escalation paths, and human-in-the-loop feedback.
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Experience operationalizing systems such as Gainsight, Salesforce, Databricks/SQL, Tableau, and marketing or engagement platforms.
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Proven ability to lead cross-functional execution when ownership is distributed, context is fragmented, and dependencies block progress.
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Strong data engineering fluency: data models, ETL/ELT, data quality, event/telemetry pipelines, production tables, schemas, and integration patterns.
Benefits & Perks Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.
About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh. In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.
How this job compares
Set against the 4,188 open Customer Success jobs on Olive Jobs, counted November 5, 2026.
- Pay
- This posting$131–207K/yr
- California median$150–200K/yr499 salary ranges
- US median$109–175K/yr3,019 salary ranges
This range's midpoint, $169K, is 3% below the California median midpoint ($175K) — in the middle half of Customer Success salary ranges in California.
- Openings
- Olive Jobs lists 663 open Customer Success jobs in California and 4,188 across the US. 16% of them nationwide are listed as remote or flexible.
- Hiring the most in California
- Amazon26 open
- Salesforce15 open
- Anthropic10 open
- Experience
- Customer Success postings that state a minimum ask for 5 years of experience at the median; the middle half ask for 3 to 7 years (3,160 postings).
- Education
- 693 of the 4,188 open Customer Success jobs (17%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 5, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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