Applied Forward Deployed Engineer

Posted 21 Hours Ago
5 Locations
In-Office or Remote
140K-180K Annually
Senior level
Big Data • Cloud • Software • Generative AI • Big Data Analytics
Monte Carlo is building the Data & AI Observability category to enable the world's enterprises to adopt trusted AI.
The Role
This role focuses on post-sale technical execution, ensuring customer onboarding and deployment, driving customer consumption of products, writing production code, diagnosing issues, and expanding adoption across teams.
Summary Generated by Built In

About Monte Carlo

Monte Carlo is the data and AI observability platform trusted by data teams at some of the world's most data-intensive companies. We help organizations find, understand, and fix data problems before they become business problems across Snowflake, Databricks, and the modern cloud data stack. Data reliability is the foundation of every AI application; Monte Carlo makes that foundation trustworthy.

Backed by Accel, Redpoint Ventures, Notable Capital, ICONIQ Growth, and Salesforce Ventures, Monte Carlo is powering the future of reliable data + AI.

The Role

We're building a new kind of post-sale technical role. Not a Support Engineer. Not a traditional CSM. An Applied Forward Deployed Engineer, someone who takes ownership the moment a deal closes and doesn't let go until the customer is fully live, deeply adopted, and driving real value from Monte Carlo.

This is a post-sale role inside our GTM organization, focused entirely on deployment, adoption, and getting customers to consumption. You'll work closely with Customer Success and Account teams, but your metric is technical — is this customer live, and are they getting value?

What You'll Do
  • Own onboarding and deployment from day one post-close — getting customers live on Snowflake, Databricks, and adjacent stack components with the right monitors, alerts, and integrations configured for their environment.

  • Drive customers to consumption — you're accountable for ensuring they're actively using what they bought and realizing measurable value, not just technically deployed.

  • Write production-quality code where needed: custom integrations, API-based automations, SDK implementations, and data quality rule deployments tailored to the customer's actual pipelines.

  • Unblock customers fast — diagnosing deployment issues, resolving edge cases, and removing whatever stands between a signed contract and a fully operational Monte Carlo environment.

  • Build adoption depth beyond the initial champion — helping customers expand usage across teams, data assets, and use cases to drive long-term stickiness.

  • Become the technical advisor customers call before they escalate — shaping how they operationalize data observability and growing into a trusted extension of their data team.

  • Feed deployment and adoption signals back to Product and Engineering — you'll have the clearest view of what's working in production and where customers get stuck.

  • Help define what great post-sale technical execution looks like as an early FDE hire — you'll shape the playbook.

What We're Looking For

Data Stack Depth

5+ years building on Snowflake, Databricks, or modern cloud data warehouse environments — not as an end user, as someone who designs, builds, and debugs on top of them. Familiarity with the tools that surround the warehouse — dbt, Airflow, Fivetran, Looker, or similar — is a strong plus.

Production Code

Comfortable writing Python and SQL and working with REST APIs in customer environments. You solve problems with code, not slides.

Customer Presence

You've owned technical relationships with enterprise customers. You can run a room of data engineers and give a crisp status update to a VP in the same week without switching personas.

Post-Sale Ownership

You've been the person accountable for getting customers from signed contract to live and adopted — whether in implementation, technical onboarding, solutions consulting, or a similar post-sale role. You know what it takes to drive consumption, not just deployment.

Ambiguity Tolerance

You've worked in environments where the playbook didn't exist yet. You didn't wait for one — you built it.

Data Quality / Observability (Strong Plus)

Familiarity with data quality concepts, pipeline monitoring, or incident response in data environments.

Education:

Bachelor's degree in computer science, data science, engineering, economics, business analytics, or a related field. What you've built and who you've helped matters more than where you studied.

This Is Not For You If
  • You measure success by go-live, not by consumption.

  • You prefer deep, isolated engineering work over customer interaction.

  • You're uncomfortable owning outcomes after handoff from Sales.

  • You need a fully defined playbook before you can move.

This role will frustrate you if any of those are true. It's built for engineers who care about outcomes, not just delivery.

Why Monte Carlo
  • Category leader in data observability — a problem that only gets harder as AI raises the stakes for data reliability.

  • Joining as an early FDE hire means real influence on how post-sale technical execution scales.

  • Tight partnership with Customer Success, Product, and Engineering — no silo, no hand-off culture.

  • Customers are data-sophisticated: you'll work with engineers who push back, which keeps the work sharp.

  • Competitive compensation, equity, and a remote-first environment with ~25% travel for customer engagement.

#LI-REMOTE

#BI-REMOTE

Come As You Are

Equality is a core tenet of Monte Carlo's culture. We are committed to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. 

Monte Carlo is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

We are proud to be recognized for our world-class employee experience:

Monte Carlo Named 2025 Databricks Data Governance Partner of the Year

We were recently recognized as the #1 Data Observability Platform by G2 for the 4th consecutive quarter. See our G2 reviews here!

Monte Carlo Named to G2's Best Software Products of 2026

Monte Carlo was featured on Database Trends and Applications (DBTA’s) Trend-Setting Products for 2025!

We are super proud to be named the 2026 Best Place to Work by Built In!

Beware of Imposter Recruiters and Job Scams

  • All official communication from our recruiting team will come from an @montecarlodata.com email address.

  • We will never ask candidates to provide sensitive personal information (such as bank details, social security numbers, or payment) at any stage of the recruitment process.

  • We will never request payment for equipment, training, or application processing.

  • Our open positions are always listed on our official careers page: https://jobs.ashbyhq.com/montecarlodata.

If you are contacted by someone claiming to represent Monte Carlo but you’re unsure of their legitimacy, please reach out to us directly at [email protected] before sharing any personal information.

Skills Required

  • 5+ years experience in modern cloud data warehouse environments (Snowflake, Databricks)
  • Comfortable writing production-quality Python and SQL
  • Experience managing technical relationships with enterprise customers
  • Accountable for getting customers live and adopted post-sale
  • Bachelor's degree in computer science, data science, engineering, or related field

What the Team is Saying

Mike Ebbers
Xuanzi Han
Cassie Quan
Tim Osborn

Monte Carlo Compensation & Benefits Highlights

  • Healthcare Strength Extensive health coverage includes medical, dental, vision, life and disability insurance, wellness programs, and mental health support. The breadth of coverage aligns with comprehensive tech-industry offerings.
  • Leave & Time Off Breadth Unlimited PTO is paired with paid holidays, sick time, and bereavement leave. Generous parental leave is also highlighted as part of the overall time-off framework.
  • Equity Value & Accessibility Company equity is included alongside core compensation. This provides long‑term upside potential as part of the total rewards package.

Monte Carlo Insights

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The Company
HQ: San Francisco, CA
221 Employees
Year Founded: 2019

What We Do

As businesses increasingly rely on data and AI to power digital products and drive better decision-making, it's mission-critical that this data is accurate and reliable. Monte Carlo, the data + AI observability leader, is the creator of the industry's first end-to-end Data & AI Observability platform. Our mission is to enable the world's enterprises to adopt trusted AI. In 2025, Monte Carlo launched Agent Observability — the first capability to unify observability across both data and AI stacks in a single platform — enabling teams to monitor, trace, and troubleshoot enterprise AI agents in production. A Forrester Total Economic Impact study found that Monte Carlo delivers a 358% return on investment. Recognition and awards: Named a CBInsights AI100 company and the "New Relic for data" by Forbes. G2 #1 Data Observability Platform for eight consecutive quarters. G2 Best Software Product of 2026. 2025 Databricks Data Governance Partner of the Year. DBTA Readers Choice for Best Data Observability Solution 2024 and DBTA Trend-Setting Product for 2025. We've raised $236M from Accel, ICONIQ Growth, Redpoint Ventures, IVP, and Salesforce Ventures. Data-driven companies like NASDAQ, Honeywell, Roche, Fox, American Airlines, and PepsiCo trust Monte Carlo to deliver reliable data and AI at scale.

Why Work With Us

A Built In 2026 Best Place to Work, Inc. Best Workplace 2024, and Newsweek Most Loved Workplace. We're remote-first, solving one of the biggest problems in the AI era: trust. We build fast, ship bold, and have a great time doing it. Come help the world adopt trusted AI.

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Employees work remotely.

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