Sr. Manager, Data Engineering New

NetVerks Inc.; India; Hybrid; INR 3,500,000 - 7,000,000; Full time

Job summary

Adobe seeks a Senior Manager to lead a blended AI engineering team building an agentic AI platform and marketing solutions on top of it. You own the roadmap, execution, and quality bar for platform engineers, applied-AI developers, and data engineers, delivering reliable production systems used by marketing and analytics teams daily.

The role emphasizes delivery leadership, architectural decision-making, and collaboration with globally distributed teams, driving real business outcomes beyond

Qualifications

• ~12+ years in software/AI/ML engineering with 4+ years in people leadership.
• Deep expertise in agentic AI / LLM systems—orchestration, retrieval/RAG, tool use, evaluation.
• Track record of shipping production AI/ML systems at scale with reliability and cost/latency awareness.
• Strong Python and cloud-native delivery with architectural judgment.

Responsibilities

• Own delivery of the AI platform, including LLM orchestration and RAG pipelines.
• Lead the team to build AI agents and workflows for marketing use cases.
• Set roadmap and planning; translate priorities into sequenced delivery.
• Represent work to leadership and cross-functional partners across a distributed org.

Skills

Agentic AI

LLM orchestration

Python

Cloud-native

Team leadership

Stakeholder management

Architecture decisions

Tools

Databricks

pgvector

Neo4j

MCP tooling

Job description

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…

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.

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

• 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 openly, separate fact from guess, flag risks early.
• Ownership — own outcomes end‑to‑end, not just handoffs; the team ships things that work and says so honestly when they don't.
• Bar‑raiser — hire people better than the current team and hold a high engineering standard.
• Builder's bias — move fast on real problems, cut scope ruthlessly, prefer working systems over polished plans.

About Adobe

Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry‑leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.
Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.

At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture, focus on people, purpose and community, Adobe for All, comprehensive benefits programs, the stories we tell, the customers we serve, and how you can help us advance our mission of empowering everyone to create.

Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more.

Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email [e-mail].

AI Use Guidelines for Interviews

Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.
At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience.