Senior Technical Architect / Vice President (AI, Cloud & LLM Platforms), VP

Position Overview

Job Title: Senior Technical Architect / Vice President (AI, Cloud & LLM Platforms), VP

Location: Pune, India

Role Description

The Senior Technical Architect / VP is responsible for defining enterprise-wide architecture vision across AI, LLM systems, cloud, data, and distributed platforms. This role leads end-to-end technical strategy, modernization, architectural governance, and oversees delivery of scalable, secure, and highperformance AI/LLM systems. The leader collaborates with product, engineering, data, ML, and executive teams to build nextgeneration AI capabilities.

What we'll offer you

As part of our flexible scheme, here are just some of the benefits that you'll enjoy

• Best in class leave policy
• Gender neutral parental leaves
• 100% reimbursement under childcare assistance benefit (gender neutral)
• Sponsorship for Industry relevant certifications and education
• Employee Assistance Program for you and your family members
• Comprehensive Hospitalization Insurance for you and your dependents
• Accident and Term life Insurance
• Complementary Health screening for 35 yrs. and above

Your key responsibilities

Architectural Leadership

• Own enterprise architecture vision across AI, LLM, cloud, data, and application stack.
• Define reference architecture, engineering standards, best practices, and technology roadmaps.
• Lead design governance, modernization programs, and crossplatform architecture reviews.
• Architect secure, scalable, highly available distributed systems.

AI & Data Platform Architecture

• Architect largescale AI platforms including ML pipelines, inference systems, and MLOps workflows.
• Define data ingestion, feature store, orchestration, and AI observability frameworks.
• Lead architecture of realtime analytics, streaming pipelines, and distributed AI workloads.

Cloud & Infrastructure Strategy

• Architect cloudnative platforms using AWS, GCP, or Azure.
• Govern IaC, DevOps, CI/CD workflows, container orchestration, and multicloud strategies.
• Drive performance optimization, cloud security, resiliency, and cost governance.

LLM Systems Responsibilities

• Architect endtoend LLM systems including RAG pipelines, prompt orchestration, and scalable inference.
• Define enterprise patterns for hosting, finetuning, optimizing, and deploying LLMs.
• Establish governance for LLM evaluation, safety, quality metrics, and hallucination reduction.
• Lead architecture for structured/unstructured data ingestion, embedding pipelines, and vector databases.
• Design LLMpowered agents, tooluse orchestrators, and workflow automation layers.
• Oversee prompt engineering standards, reusable libraries, and guardrail-enabled prompts.
• Implement LLM observability: drift detection, token usage, latency, and cost optimization.
• Define frameworks for responsible AI: bias, fairness, compliance, toxicity control, auditability.

Engineering Excellence & Strategy

• Lead design of missioncritical systems with strong performance, availability, and faulttolerance.
• Evaluate emerging AI/LLM, cloud, and DevOps technologies for enterprise adoption.
• Drive engineering standards, coding guidelines, performance benchmarks, and operational best practices.

Stakeholder & Team Leadership

• Advise senior leadership on technology strategy and investments.
• Mentor architects, principal engineers, and technical leaders.
• Align globally distributed engineering teams to architectural direction.
• Ensure compliance with regulatory, audit, and security requirements.

Your skills and experience

• 12-20+ years of enterprise architecture, AI, cloud, or large-scale engineering leadership.
• Expertise with distributed systems, microservices, APIfirst design, and event-driven architectures.
• Strong hands-on knowledge of LLM/AI architecture, RAG, vector search, and inference optimization.
• Proficiency in Python, Java, or Node.js for architecture prototyping.
• Deep experience with Kubernetes, Docker, Terraform, Helm, cloud networking & security.
• Strong understanding of ML workflows, MLOps frameworks, model registries, and monitoring.
• Experience with big data tools (Kafka, Spark, NoSQL systems).
• Excellent leadership, communication, and executive stakeholder management skills.

How we'll support you

• Training and development to help you excel in your career
• Coaching and support from experts in your team
• A culture of continuous learning to aid progression
• A range of flexible benefits that you can tailor to suit your needs

About us and our teams

Please visit our company website for further information:

We strive for a in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.
Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.
We welcome applications from all people and promote a positive, fair and inclusive work environment.