Forward Deployed Engineering Manager
Databricks is hiring a Forward Deployed Engineering Manager in London, United Kingdom. Level rates it ; you can apply on Databricks.
Level's read on this job
- Works on AI ●●●○ is how Level rates this forward deployed engineer role: the daily work is on AI products, without building the model.
- The posting mentions MLOps among its tools and skills.
- Level classes it as a senior role.
- Databricks has 894 other open roles on Level.
- Posted in the last few days.
AI in this role
Req ID: CSQ128R179
Location: London, United Kingdom - Hybrid
Recruiter: Dina Hussain
Role Overview
As a Forward Deployed Engineering (FDE) Manager, you will lead a high-performing delivery team of 8+ Individual Contributors (ICs) to build and productionize solutions for customers' data and AI challenges using the Databricks platform. You are responsible for ensuring high-quality technical execution, driving professional services business outcomes, and nurturing elite engineering talent while remaining close to the technology and execution.
Scope of Impact & Leveling Criteria
- Oversees successful delivery at the delivery team and account level, driving Professional Services (PS) business outcomes through high-quality execution. Impact is measured by key metrics including Bookings, Revenue, Margin, CSAT, and Direct Consumption / Delta Cloud Consumption (DBUs).
- Typically manages an elite engineering team of 8+ Individual Contributors. Handles delivery across direct accounts and navigates technical and scoping alignment with Engagement Managers and client stakeholders.
- Focuses internally on building team capabilities and externally on account execution. Mandates high standards for Greenhouse scorecards and interview calibrations, ensuring clear pass/fail hiring signals.
Key Responsibilities & Core Behaviors
- Connect your team’s day-to-day work to real customer outcomes and business impact. Build excitement about Databricks by sharing customer wins and delivery successes, making each individual feel motivated and appreciated.
- Reinforce your team’s top delivery priorities. Help your team focus on high-impact technical work, redirecting effort away from low-value tasks and removing blockers that slow execution. Use delivery data and PS KPIs to confirm focus areas.
- Hire strong PS talent using structured interviews and practical delivery scenarios. Ensure team takes 2–4 protected hours a week for continuous technical learning and experimentation. Understand your team’s strengths and growth areas to provide regular coaching, and handle underperformance early with clear feedback and accountability.
- Remove delivery blockers quickly, using simple automation or AI assistants to accelerate routine work. Run consistent inspection rhythms (standups, project reviews, retrospectives) and hold teammates strictly accountable to timelines and quality bars.
- Translate Databricks’ Culture Principles (Customer Obsessed, Truth Seeking, First Principles, Raise the Bar, Company-First, Bias for Action) into concrete day-to-day behaviors, ensuring standards are upheld in all customer interactions.
- Apply a builder and AI-first mindset to improve team productivity. Review delivery plans and architectures utilizing practical knowledge of the Databricks platform and cloud environments (AWS, Azure, GCP). Actively coach ICs on secure, scalable deployment patterns, governance, and production readiness.
What We Look For
- Experience: 8+ years of total technical experience with 2+ years of experience managing, leading, or mentoring high-caliber technical teams in data engineering, data platforms, software engineering, or AI/ML.
- Technical Depth: Strong technical background capable of evaluating architectures spanning distributed computing (Apache Spark™), Python/Scala, modern cloud ecosystems (AWS, Azure, GCP), CI/CD, and MLOps/GenAI frameworks.
- Leadership Skills: Proven ability to manage technical project delivery, timelines, scoping, conflict resolution, and executive customer relationships from technical ICs up to Director level.
- Certifications: Databricks Certification required (or path to completion).
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
How we rate this
Forward Deployed Engineering Manager at Databricks rates 64 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in forward deployed engineer jobs at this level
Pay
- Typical forward deployed engineer job
- $180k
This posting doesn't list pay. Use the typical forward deployed engineer figure when pay comes up. See forward deployed engineer jobs
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: ML Ops. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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