AI forward deployed engineering manager at Databricks Bengaluru, leading the customer-facing team that productionizes first-of-its-kind GenAI applications.

This full-time Bengaluru role was posted on 30 September 2026. The listing describes the AI FDE team, which delivers professional services engagements helping customers build and productionize GenAI applications, and seeks a leader to grow and scale that team: hiring, mentoring, and building the team, plus shaping cross-functional collaboration with Product, R&D and GTM. Requirements include experience building and managing high-performing teams of AI/ML scientists, engineers and leaders, and the ability to scope, sell and deliver technical engagements in enterprise environments, including managing escalations.

About Databricks

Databricks builds a data and AI platform around the lakehouse architecture, combining data warehousing and data lakes for analytics, data engineering and machine learning. The company was founded by the creators of Apache Spark.

Databricks has a large engineering presence in Bengaluru, with listings spanning platform engineering, monitoring and reliability, and customer-facing engineering roles. Learn more on Databricks's website.

The role in plain terms

The scope-sell-deliver triad makes this a services-leadership role with commercial accountability, not a pure engineering management seat - you carry engagements from pre-sales scoping through delivery and escalations. First-of-its-kind GenAI work means the playbook is being written as you go, and the team-leadership requirement spans scientists, engineers and leaders, indicating a multi-level organization.

The team and the work

Per the listing, the team works cross-functionally with AI Product, Research and Engineering, so the role channels customer reality back into product direction. The enterprise-environment requirement is explicit.

What the employer asks for

These requirements are quoted from the employer's listing, kept in their exact words so eligibility details are not distorted:

Experience building and managing high-performing teams of AI/ML scientists, engineers, and leaders
Ability to scope, sell, and deliver technical engagements in enterprise environments, including managing escalations and ensuring successful customer outcomes
Strong, current technical depth in AI/ML foundations, with the ability to contribute meaningfully in architecture reviews and the curiosity to stay current as the field...
Experience leading teams that have shipped production AI solutions in cloud environments (AWS, Azure, or GCP)
Proven success developing strategy with senior executive stakeholders to define program-level goals, align technical vision, and build trust throughout complex enterprise engagements
Experience driving AI transformation across enterprise customers, spanning applied AI product management, organizational change management, and stakeholder alignment
Experience working across Sales, Product, and GTM to connect AI delivery to business outcomes
Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience

Who this role suits

Engineering managers with AI/ML team-building experience and a track record delivering customer-facing technical engagements in enterprises. Not for managers without commercial/scope-to-deliver services experience, or AI managers who want to avoid customer escalation ownership.

Practical notes

For FDE leadership roles, expect questions on an engagement you scoped and delivered, an escalation you defused, and how you hire for ambiguous technical work. Metrics from teams you built matter.

Working at Databricks

Work at Databricks centres on large-scale data systems: query engines, orchestration, observability and the infrastructure that runs customer data and AI workloads.

How to apply

Apply directly on the employer's site: AI Forward Deployed Engineering Manager at Databricks. We found this listing on the Greenhouse public job board (databricks.com), where it was posted on 30 Sep 2026 and was still open when we checked on 30 Oct 2026. Before applying, re-read the employer's own description in full, since eligibility details, deadlines and process steps can change at any time and the employer's page is always the final word. Tailor your resume to the specific requirements above rather than sending a generic one: mirror the skills and tools the listing names where you genuinely have them. A short, specific note on why this team and this problem interest you goes further than a long generic cover letter. Never pay a fee to apply or interview; genuine employers, including this one, do not charge candidates.

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This is our short summary of the employer's listing. The full description, eligibility and deadline are on the employer's page.