Staff Product Manager

MongoDB
Full-timeProduct / OwnerDublin, Ireland · Remote within Ireland · Hybrid
Apply Now

TechJobs.ie Job Insights

At a glance

Employment type
Full-time
Workplace
Hybrid

Technologies & skills

Cloud & infrastructure

What you'll be doing

Lead the strategy for MongoDB's observability products, transforming raw telemetry into AI-powered diagnostics and autonomous remediation. Define vision, roadmap, and product experiences for database health, performance diagnostics, and data visualization. Mentor PMs and partner with engineering, design, and stakeholders.

  • Define vision, strategy, and roadmap for MongoDB observability
  • Shape AI-powered observability features such as anomaly detection and automated root cause analysis
  • Own product strategy for database health, diagnostics, alerting, log analysis, and data visualization
  • Identify high-impact opportunities across the observability stack
  • Lead customer discovery and turn insights into product decisions
  • Partner with engineering and design to deliver products
  • Establish success metrics and evaluate progress
  • Communicate product direction to senior leaders and stakeholders

Key requirements

Must-have

  • 10+ years of product management experience
  • Experience leading complex technical products in data management or analytics
  • Track record of defining strategy and delivering products for technical audiences
  • Ability to translate ambiguous problems into strategies and execution plans
  • Ability to lead through influence across teams
  • Excellent customer instincts and communication skills
  • Experience launching products requiring behavior change or ecosystem coordination
  • Comfort with AI-enabled product experiences

Nice-to-have

  • Familiarity with observability tools such as CloudWatch, Datadog, Grafana, Splunk, OpenTelemetry
  • Experience building or scaling telemetry infrastructure or data pipelines
  • Familiarity with MongoDB, Atlas, or similar database products
  • Experience leading product strategy for AI-assisted workflows or intelligent diagnostics

Experience: 10+ years of product management experience, including leading complex technical products in data management or analytics

Role signals

Technical focus
product management for observability, data, and AI-powered diagnostics
Leadership
Mentoring
Architecture / system design
Indicated in the listing
Hands-on vs management
Hands-on

Full job description

The observability market is shifting from surfacing data to delivering answers. MongoDB is looking for a Staff Product Manager to lead that shift for database users, owning the strategy that takes customers from raw telemetry to AI-powered diagnostics and autonomous remediation, so developers can focus on building great applications instead of managing infrastructure.

You will define how MongoDB turns raw telemetry into actionable intelligence, set the vision for AI-powered root cause analysis and proactive recommendations, and shape what best-in-class database observability looks like at global scale.

The ideal candidate has experience shipping products that deal with data at scale, can engage deeply with senior engineering on technical architecture, and knows how to balance long-term platform investment against near-term customer value.

We are looking to speak to candidates who are based in Dublin for our hybrid working model.

What you'll do

  • Define the vision, strategy, and multi-year roadmap for MongoDB observability, balancing the needs of developers, ops teams, enterprise customers, and internal engineering teams

  • Help shape the next generation of AI-powered and agentic observability, including intelligent anomaly detection, automated root cause analysis, and proactive recommendations that help customers resolve issues before they escalate

  • Own product strategy for experiences that span database health, performance diagnostics, alerting, log analysis, and data visualization, creating a coherent observability journey rather than a collection of disconnected tools

  • Identify high-impact opportunities across the observability stack, from how customers monitor and understand their deployments to how MongoDB can reduce the operational burden of managing a database fleet at scale

  • Lead customer discovery with developers, DBAs, and enterprise teams; turn qualitative and quantitative insights into clear product decisions that reduce time spent managing the database and increase time spent building applications

  • Partner deeply with engineering and design to frame problems, define requirements, make tradeoffs, and deliver high-quality products from discovery through launch and iteration

  • Establish clear success metrics for observability, using product analytics, customer feedback, research, and market signals to evaluate progress and adjust priorities

  • Communicate product direction and decisions clearly to senior leaders and cross-functional stakeholders, including the rationale behind what we will and will not build

  • Raise the bar for product management by mentoring other PMs, improving product practices, and modeling strong judgment, customer empathy, and execution

What you'll bring

  • 10+ years of product management experience; including experience leading complex technical products in the data management or analytics space

  • A track record of defining strategy and delivering products used by technical audiences, ideally across database, data infrastructure, or observability

  • Experience translating ambiguous customer and business problems into focused strategies, product narratives, roadmaps, and prioritized execution plans

  • Demonstrated ability to lead through influence across multiple engineering and product teams without relying on formal authority

  • Excellent customer instincts and the ability to move comfortably between user research, product details, business strategy, and executive communication

  • Experience launching products that require behavior change, ecosystem coordination, or adoption across both self-serve and enterprise customers

  • Comfort working with AI-enabled product experiences and evaluating where automation, guidance, and human control create the most value

  • Exceptional written and verbal communication skills, with the ability to make complex technical concepts clear and compelling

  • A bias toward action, disciplined prioritization, and the judgment to make decisions with incomplete information

Nice to have

  • Familiarity with observability tools and platforms such as CloudWatch, Datadog, Grafana, Splunk, OpenTelemetry

  • Experience building or scaling telemetry infrastructure, data pipelines, or platform products used by other engineering teams

  • Familiarity with MongoDB, Atlas, or comparable database products and the operational challenges customers face managing them at scale

  • Experience leading product strategy for AI-assisted workflows, anomaly detection, or intelligent diagnostics

How success will be measured

  • Customers move from reactive troubleshooting to proactive optimization, with Atlas surfacing insights and recommendations before issues escalate

  • AI-powered diagnostic experiences deliver meaningful reductions in time-to-resolution while remaining transparent and easy to act on

  • Adoption, engagement, and customer satisfaction improve across observability workflows including alerting, performance diagnostics, and proactive database optimization

  • The observability roadmap is clear, well-sequenced, and trusted by engineering, design, and go-to-market partners

  • Enterprise customers successfully adopt new observability capabilities while the platform remains accessible to developers who are not database or infrastructure experts

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 67,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID: 3273513808

Interview prep pack

Grounded in this listing. Use it to prepare examples before you apply.

Your interview focus

You will define and execute the product strategy for MongoDB's observability platform, focusing on AI-powered diagnostics, proactive recommendations, and seamless experiences for database users at scale. Expect deep engagement with engineering, customers, and cross-functional teams.

  • Observability strategy·High
  • AI-powered diagnostics·High
  • Database performance·High
  • Customer-centric product leadership·High

Only have 30 minutes?

Follow a focused preparation plan based on this job.

Start 30-minute prep

Your 30-minute plan

  1. Review MongoDB Observability Offerings

    0–8 min

    Study Atlas observability features, documentation, and recent product updates to understand current capabilities and gaps.

  2. Prepare Product Strategy Examples

    8–15 min

    Identify and outline 1-2 stories where you set vision, prioritized, and delivered complex technical products.

  3. Refresh on AI in Observability

    15–23 min

    Review how AI is used for diagnostics, anomaly detection, and recommendations in observability platforms.

  4. Reflect on Cross-Functional Leadership

    23–30 min

    Recall specific examples of influencing engineering, design, and go-to-market teams to deliver impactful products.

Likely questions

, 8 items

Priority reflects how strongly this topic is emphasised in the job listing, not whether it will be asked.

Talking points

, 6 items
  • Defining Product Strategy for Observability

    You will own the vision and roadmap for MongoDB's observability platform, so you must demonstrate strategic thinking and prioritization in a complex technical domain.

  • AI-Powered Diagnostics & Automation

    The role emphasizes AI-driven root cause analysis, anomaly detection, and proactive recommendations. Understanding how to apply AI in observability is central.

  • Database Health and Performance Monitoring

    You will shape experiences around database health, diagnostics, alerting, and log analysis, requiring expertise in these areas.

  • Customer Discovery & Translating Insights

    Turning qualitative and quantitative feedback into actionable product decisions is a core responsibility.

  • Cross-Functional Leadership & Influence

    You must lead across engineering, design, and go-to-market teams without formal authority, making collaboration and influence key.

  • Success Metrics & Product Analytics

    Establishing and tracking metrics for adoption, engagement, and satisfaction is critical to measuring impact and guiding priorities.

What to research

, 3 items
  • AI-Driven Observability and Diagnostics

    The role emphasizes shaping AI-powered root cause analysis, anomaly detection, and proactive recommendations. Be ready to discuss how you have applied or would apply AI to observability challenges.

  • Defining and Communicating Product Strategy

    You will own the multi-year vision and roadmap for observability. Prepare to articulate your approach to strategy, prioritization, and stakeholder alignment in technical product domains.

  • Cross-Functional Influence Without Authority

    Success depends on leading across engineering, design, and go-to-market teams. Be ready with examples of influencing outcomes and building consensus without direct authority.

Questions to ask

, 6 items
  1. How does MongoDB define success for observability products in the next 12-24 months?

    Why ask this? Clarifies expectations and how your impact will be measured.

  2. What are the biggest technical or organizational challenges facing the observability team today?

    Why ask this? Reveals current pain points and where you can add value.

  3. How do engineering and product teams collaborate on AI-driven features?

    Why ask this? Shows how cross-functional work happens on complex, innovative projects.

  4. What feedback have you received from customers about current observability workflows?

    Why ask this? Helps you understand user pain points and priorities.

  5. How does MongoDB support product managers in mentoring and developing others?

    Why ask this? Clarifies opportunities for leadership and professional growth.

  6. What is the process for prioritizing the observability roadmap across different user segments?

    Why ask this? Gives insight into decision-making and stakeholder management.

Register now to upload your CV

Create a free account, save a PDF or Word CV, and quick apply on roles that take applications here.

Apply NowApply before: 7 Oct 2026