TELUS Digital
Website:
telusdigital.com
Job details:
Engineering Manager- AI with Data Engineers, DevOps, and Microservices
Location: Hybrid (Bangalore)
Duration: Full-time- Permanent
People & Team Leadership
- Manage and grow a high-performing team of engineers (Developers, Data Engineers, DevOps), providing regular 1:1s, coaching, feedback, and career development.
- Create a culture of ownership, learning, and psychological safety where engineers feel empowered to improve the platform and challenge the status quo.
- Drive hiring, onboarding, and performance management for the team, setting clear expectations and outcomes.
Required Qualifications
- 10–15 years of industry experience building and operating cloud-based products or platforms.
- 3–5+ years of experience in people management (not just tech lead), ideally in Developer & DE Experience domains.
- Strong hands-on background with modern DevOps practices: CI/CD pipelines, infrastructure-as-code, container orchestration (e.g., Kubernetes) or serverless, cloud platforms (AWS/Azure/GCP), and observability stacks.
- Proven experience designing or evolving internal platforms/tools used by many product teams (e.g., deployment platforms, service templates, shared libraries, internal CLIs).
- Solid understanding of software engineering fundamentals (APIs, microservices, distributed systems, security basics) and ability to review designs and code at a high level.
- Demonstrated ability to set direction, manage stakeholders, and drive alignment across multiple teams and functions.
- Excellent communication skills, with the ability to translate technical trade-offs into clear options for engineering and business stakeholders.
Nice-to-Have
- Experience in a Staff/Principal Engineer or Tech Lead role before moving into management.
- Prior work in Developer Productivity/Enablement, Platform Engineering
- Exposure to policies and tooling around SDLC governance, security controls, and compliance (e.g., audit trails, approvals, policy-as-code).
- Experience with data platforms or analytics pipelines supporting engineering metrics and observability.
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