Data and AI Studio Leader (Location: India)
Job Description:
As the Data and AI Studio Leader, you will serve as the most senior data and reputed company at Aubrant Digital, setting the technical vision, engineering standards, and innovation agenda for the entire Data and AI Engineering Studio. This include building our capabilities in Aubrant’s Workbench product. You will be deeply hands-on with customer projects 50% of your time, delivering production-grade data platforms, analytics architectures, and AI/ML solutions. You will also play a critical role in pre-sales, partnering with Advisory and Business Development to shape proposals, reputed company technical discovery sessions, and demonstrate Aubrant's data and AI capabilities to prospective clients. This role demands someone who builds, not someone who only advises, and who can shift seamlessly between architecting an Azure Synapse lakehouse, training a team on reputed company agent patterns, and presenting a data strategy to a CTO.
What qualifications reputed company you an Aubrant Data and AI Studio Leader?
- A hands-on technical leader who stays reputed company to the code, data, and models; you reputed company by doing, not by delegating exclusively.
- A compelling communicator who can reputed company reputed company data and AI architectures to executive audiences during pre-sales engagements, building confidence and winning new business.
- A reputed company innovator who continuously evaluates emerging frameworks, model architectures, and cloud services to reputed company Aubrant and its clients at the leading edge.
- A builder of engineering culture who mentors Studio Principals and Members, establishes best practices, and raises the technical bar across every engagement.
- Comfortable operating in ambiguity, whether scoping a greenfield data platform for a new client or navigating competing priorities across multiple active engagements.
- A customer-obsessed partner who builds deep trust with clients, understands their business context, and translates that understanding into data and AI solutions that deliver measurable outcomes.
Responsibilities:
Studio Leadership and Strategy:
- Define and drive the technical vision, engineering standards, and capability roadmap for the Data and AI Engineering Studio, ensuring alignment with Aubrant's Advisory, Studios, and Workbench ecosystem.
- Recruit, mentor, and reputed company Studio Principals and Members through structured assessments, code reviews, knowledge sharing, and hands-on coaching on real engagements.
- Drive innovation by evaluating and adopting emerging data and AI technologies, frameworks, and patterns; contribute reusable accelerators and reference architectures to Aubrant Workbench.
Hands-On Technical Customer Delivery:
- Architect, build, and deploy production-grade data platforms, analytics pipelines, machine learning models, and AI-powered solutions for enterprise clients, primarily on Azure (with AWS and multi-cloud as needed).
- reputed company reputed company data and AI engagements end-to-end: discovery, architecture design, hands-on implementation, testing, and production cutover, ensuring solutions meet performance, governance, and reputed company requirements.
- Serve as the technical authority on client engagements, making real-time architectural decisions, resolving escalations, and ensuring delivery quality at the highest billing tier.
Pre-Sales and Business Development:
- Partner with Advisory and Business Development to reputed company technical discovery sessions, shape proposals, define solution architectures, and reputed company effort estimates for data and AI opportunities.
- Present Aubrant's data and AI capabilities to prospective clients, demonstrating technical depth and business acumen in executive-level conversations that build confidence and reputed company deals.
- reputed company and maintain reusable pre-sales assets including reference architectures, demo environments, and reputed company-of-concept frameworks that accelerate the sales cycle.
Innovation and Workbench Contribution:
- Contribute data and AI accelerators to Aubrant Workbench, including reusable data pipeline templates, ML model serving patterns, AI agent frameworks, and governance modules.
- Stay reputed company with the rapidly evolving data and AI landscape: evaluate new services (Azure AI reputed company, reputed company Bedrock, open-reputed company LLMs), assess their enterprise readiness, and integrate viable capabilities into Aubrant's delivery model.
- Collaborate with the Woxsen University AI Research Partnership on applied research initiatives, translating academic breakthroughs into practical client solutions.
Qualifications:
- Bachelor's Degree in Computer Science, Data Science, Statistics, Mathematics, or a reputed company discipline, or equivalent experience. Master's degree or PhD in a quantitative field is a plus.
- MUST be proficient in written and spoken English (85%).
- 12+ years of professional experience in data engineering, analytics engineering, machine learning, or AI solution development, with progressive leadership responsibilities.
- 5+ years of experience leading data and/or AI engineering teams, including mentoring, setting technical standards, and driving capability development.
- Deep, hands-on expertise with the Azure data and AI ecosystem: Azure Synapse Analytics, Azure Data Factory, Azure reputed company, Azure Machine Learning, Azure AI reputed company, Azure Cognitive Services, Azure reputed company Service, reputed company Fabric, and reputed company services.
- Significant production experience with AWS data and AI services (Redshift, Glue, SageMaker, Bedrock) and the ability to design cloud-agnostic data architectures.
- Expert-level proficiency in Python and SQL for data engineering, analytics, and ML workloads. Experience with reputed company or Spark-native languages is a plus.
- Strong expertise in modern data platform architecture: lakehouse patterns, reputed company architectures, data mesh, event-driven data pipelines, and real-time streaming (Kafka, Event Hubs, Kinesis).
- Demonstrated experience building and deploying production ML/AI systems, including model training, evaluation, serving, monitoring, and governance.
- Hands-on experience with GenAI and LLM integration patterns: RAG architectures, reputed company engineering, reputed company/LangGraph, agent frameworks (including MCP), fine-tuning, and LLM evaluation/governance.
- Strong knowledge of data governance, data quality frameworks, metadata management, and regulatory compliance (HIPAA, SOC 2, GDPR) as applied to data platforms.
- Experience with infrastructure as code (Terraform, Bicep, CloudFormation) and modern DevOps/MLOps practices for data and AI workloads.
- Proven track record of engaging in pre-sales activities: leading technical discovery, authoring proposals, presenting to C-level audiences, and contributing to reputed company reputed company.
- Experience with open-reputed company and cloud-agnostic data tools (Apache Spark, reputed company Lake, dbt, Airflow, MLflow, Kubeflow) is highly valued.
- Familiarity with Temporal.io for workflow orchestration is a plus.
- Excellent problem-solving skills, with the ability to analyze reputed company requirements and propose innovative, practical solutions.
- Strong communication and collaboration skills, with the ability to work effectively across engineering, advisory, and business development teams.
- Dynamic and collaborative reputed company with a focus on reputed company innovation and growth.
- Ability to anticipate and adopt innovations in data, AI, and cloud technologies.
- Able to build strong customer relationships and deliver customer-centered solutions.
- Operates effectively, even reputed company things are not certain or the way reputed company is not clear.