# Sr. Manager, Data Engineering at Adobe

Adobe is hiring a Sr. Manager, Data Engineering in Bengaluru, India. Level rates it Builds AI ●●●●; you can [apply on Level](https://jobsbylevel.com/go/9fbbb2c6-70be-4cf1-bbbd-ecd1bff0437b).

AI Level 4, AI centrality 86 out of 100. Bangalore.

## Details

- Company: [Adobe](https://jobsbylevel.com/companies/adobe)
- AI level: AI Level 4 (score 86 out of 100)
- Location: Bangalore
- Posted: October 11, 2026
- Apply: https://jobsbylevel.com/go/9fbbb2c6-70be-4cf1-bbbd-ecd1bff0437b

## Description

Role Summary We're looking for a Senior Manager to lead a blended AI engineering team building the agentic AI platform and the marketing solutions that run on top of it. This is a delivery-leadership role: you own the roadmap, execution, and quality bar for a team of platform engineers, applied-AI solutions builders, and data engineering — turning cutting-edge agentic AI into reliable, production systems that marketing and analytics teams depend on every day. You will operate at the intersection of platform and product: hardening the agentic infrastructure (LLM orchestration, retrieval, tool/MCP integration, deploys, reliability) while making sure the AI solutions built on it deliver real marketing outcomes. You'll grow the people on your team, set a high engineering bar, and partner across a global AI organization. What You'll Do Platform & infrastructure Own delivery and reliability of the agentic AI platform: LLM orchestration, retrieval/RAG pipelines, tool and MCP integration, model routing, and evaluation. Drive engineering quality — test discipline, deployment safety, observability, cost and latency management — across everything the team ships. Set technical direction with your senior engineers; make the hard architecture calls and unblock the team (design-level involvement; not expected to write production code day-to-day). Applied AI solutions Lead the team that builds AI agents and workflows for marketing use cases (analytics, paid media, content-to-intent, executive reporting) on top of the platform. Ensure solutions are grounded in real business outcomes and adopted by stakeholders — not demos that stall. Balance platform investment against solution delivery so both advance. People leadership & delivery Manage, coach, and grow a blended team; run hiring to build out the function. Own the roadmap and quarterly planning; convert ambiguous priorities into committed, sequenced delivery. Represent the team's work to leadership and cross-functional partners; drive alignment across a globally distributed AI organization. The Team You'll Lead A blended engineering team of: Agentic AI / platform engineers — Python, LLM orchestration, RAG, MCP/tooling, cloud-native deploys. Applied-AI solutions builders — wiring AI to marketing and analytics use cases. Data engineering — the pipelines and semantic layer the AI grounds on. Must-Have Qualifications ~12+ years in software / AI/ML engineering, with 4+ years managing engineering teams (including hiring and growing engineers). Demonstrated depth in agentic AI / LLM systems — orchestration, retrieval/RAG, tool use, agent frameworks, and evaluation of AI quality. Track record of shipping production AI/ML systems at scale — reliability, deployment safety, cost/latency awareness — not just prototypes. Strong Python and modern cloud-native / containerized delivery. Ability to set a high engineering bar and make sound architecture decisions while leading primarily through the team. Excellent communication and stakeholder management across a globally distributed organization. Preferred Qualifications Marketing technology or analytics domain experience — AEP / AJO / CJA, adtech, or digital marketing analytics. Experience with Databricks, vector databases (pgvector), graph stores (Neo4j), or similar data/AI infrastructure. Hands-on with agent/LLM frameworks and MCP, prompt/eval tooling, and LLM cost governance. Experience standing up or scaling a new AI engineering function. What Success Looks Like (First 6–12 Months) A team operating with a clear roadmap, predictable delivery, and a visibly higher quality/reliability bar. At least one AI solution moved from concept to in-production use, adopted by marketing/analytics stakeholders. Platform reliability, evaluation, and cost/observability practices established as the default, not the exception. Key hires made; team members growing and taking on larger scope. Leadership Behaviors Candor and clarity — lead with the bottom line, disagree

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/sr-manager-data-engineering-at-adobe-19965b

Source: https://jobsbylevel.com/jobs/sr-manager-data-engineering-at-adobe-19965b

## Cite this page

Level. https://jobsbylevel.com/jobs/sr-manager-data-engineering-at-adobe-19965b.

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