Technology Manager/Senior Manager - AI Platform Engineering

We are hiring Manager Technology - AI Platform Engineering for our client based at Hyderabad.

Requirements:

- Enterprise adoption strategy - driving migration, modernization, and platform adoption at scale

- AWS-centric platform architectures including data lake, developer platform, and next-generation IaC-based accelerators - Terraform and CloudFormation, Git/GitLab, AI-enabled developer platforms.

- AI-enabled developer productivity and platform acceleration (Knowledge Graph, Duo Agent Platform, Backstage Golden Paths, AI-based adoption accelerators)

- The Manager Technology Data Lake is responsible for leading engineering teams that build and operate enterprise-scale data lake platforms.

- The role drives platform strategy, engineering excellence, stakeholder engagement, cloud modernization, and data governance while ensuring reliable, secure, and scalable data services across global teams.

- Must have strong experience of AWS cloud services and core technologies supporting enterprise Data Lake architectures.

- Observability, Reliability & SRE: Apply Site Reliability Engineering (SRE) principles, monitoring, logging, alerting, and operational excellence to Data Lake platforms.

- Strategy & Prioritization: Define technology roadmaps aligned with business priorities while balancing platform stability, innovation, feature delivery, and technical debt management.

- Lead, mentor, and grow engineering teams and technical leads. Drive performance management, career development, and foster a culture of ownership, collaboration, and data quality.

- Partner with business stakeholders to translate business requirements into scalable platform capabilities. Manage expectations across analytics, machine learning, finance, compliance, and executive leadership.

- Experience managing globally distributed engineering teams across multiple regions and time zones.

- Experience with ServiceNow, organizational change management, and enterprise platform adoption strategies.

- Hands-on knowledge of Python, SQL, and modern analytics platforms supporting enterprise data ecosystems.

- Data Governance & Metadata Management: Experience implementing data governance frameworks, semantic layers, metadata management, business glossaries, and data catalog solutions.