Senior Manager, Software Engineering
Penguin Solutions (company site, opens in a new tab)15+ yrsBengaluruHybridDirect career pageEst. 35–60 LPA
Posted 10h ago
Reach people at Penguin Solutions
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Penguin Solutions you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead and grow software engineering teams responsible for core components of the ClusterWareAI platform focused on large-scale AI infrastructure deployment and orchestration.
- Drive technical execution from architecture through production, including productionizing ML, GenAI, and agentic AI capabilities with Data Science and AI teams.
- Establish engineering practices and standards for scalable, reliable, secure cloud-native distributed systems including Kubernetes, APIs, and infrastructure orchestration.
Minimum Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or related technical field, or equivalent experience.
- 15+ years software engineering experience in enterprise software, distributed systems, cloud platforms, or infrastructure software.
- 5+ years engineering leadership experience managing high-performing software engineering teams.
- Practical exposure to Data Science, Machine Learning, Generative AI, or AI/ML platforms.
Ideal Candidate Profile
- Experienced in leading complex software engineering initiatives for distributed AI infrastructure platforms with scalability, reliability, and multi-tenant considerations.
- Strong technical leader familiar with Kubernetes, cloud-native architectures, microservices, and AI-assisted software development workflows.
- Skilled in collaborating across Product Management, Architecture, Data Science, and globally distributed teams to align engineering execution with product and customer needs.