Lead Software Engineer
Electrolux Group (company site, opens in a new tab)8+ yrsBengaluruOn-siteDirect career pageEst. 30–45 LPA
Posted 21h ago
Reach people at Electrolux Group
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 Electrolux Group 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 design, build, and delivery of cloud-native consumer engagement and digital experience applications and services, owning end-to-end lifecycle from architecture to production support.
- Define and implement scalable, secure, and resilient technical architectures for new capabilities including data pipelines, event platforms, and AI-powered personalization and activation systems.
- Partner with cross-functional teams to translate business opportunities into production-ready AI-driven solutions while ensuring compliance with privacy and security regulations.
Minimum Requirements
- 8+ years of software engineering experience building and operating cloud-native applications at scale.
- Proven hands-on experience with Python and/or Go; experience delivering production solutions on Azure or GCP.
- Strong knowledge of distributed systems architecture, APIs, microservices, data pipelines, SQL, observability, CI/CD, security, and operational excellence.
- Location: Bangalore, India (onsite requirement).
Ideal Candidate Profile
- Experienced technical leader capable of influencing multi-team architecture decisions without direct authority.
- Technical expertise in AI-powered systems including LLM applications, recommendation systems, predictive models, or intelligent automation at production scale.
- Background in consumer data platforms, event streaming, data engineering tools (e.g., Kafka, Databricks), and cloud-native engineering for global consumer-facing products.