Senior Software Engineer (Full stack)

Enphase Energy is a global energy technology company and a leading provider of solar, battery, and electric vehicle charging products. Founded in 2006, our innovative microinverter technology revolutionized solar power, making it a safer, more reliable, and scalable energy source. Today, the Enphase Energy System enables users to make, use, save, and sell their own power. Enphase is also one of the most successful and innovative clean energy companies in the world, with more than 80 million products shipped across 160 countries.

Join our dynamic teams designing and developing next-gen energy technologies and help drive a sustainable future!

This role at Enphase requires working onsite 3 days a week, with plans to transition back to a full 5 day in office schedule over time.

About the role

The Cloud R&D team at Enphase nurtures cutting-edge technologies, working closely with various business units to integrate them seamlessly across our product portfolio. We are actively expanding our Cloud R&D organization and seeking an experienced Senior Software Engineer who thrives in a multi-technology environment. Success in this role requires both breadth and depth across IoT, Cloud, and Mobile domains, alongside hands-on expertise in multiple programming languages. You will contribute to the architecture, design, and implementation of high-performing, maintainable cloud and web applications, leveraging modern AI-assisted engineering tools to accelerate development and elevate code quality. You will partner with Product Managers, Analysts, and Architects to drive concepts from prototype to launch, ensuring that technology upgrades and architecture migrations are strategically planned and executed.

What you will do

• Design and implement scalable, reliable, and secure applications and services across microservices, batch jobs, web applications, data processing, and IoT device integration.
• Deliver distributed computing platforms utilizing Open Source, Data, and Cloud technologies, with a strong focus on AWS.
• Leverage AI-assisted software engineering workflows (e.g., GitHub Copilot, Cursor, Devin, Claude Code ChatGPT) to accelerate prototyping, automate testing, and optimize code refactoring.
• Champion best-in-class software engineering processes, including clean code principles, Test-Driven Development (TDD), monitoring, and performance benchmarking.
• Lead the productization of assigned projects utilizing various open-source tools, ensuring high availability for features handling millions of requests daily.
• Collaborate with DevOps teams to provide deep insights into the scalability of cloud-native technologies and streamline CI/CD pipelines.
• Maintain rigorous version control and branching strategies utilizing Git.
• Contribute to internal knowledge sharing through technical blogs, documentation, and stakeholder presentations.

Who you are and what you bring

• Master's degree (IS, CS, E&C) with 6+ years of experience, or a B.Tech (IS, CS, E&C) with 8+ years of experience from a reputed institute.
• Robust programming expertise in Java (Spring Framework, Spring Boot), Python (FastAPI, Django) or any combination of programming languages.
• High proficiency in modern code editors and IDEs (e.g., VS Code, IntelliJ IDEA, PyCharm, Devin, Claude Code, Cursor) and experience integrating AI-assistive plugins to maximize developer productivity.
• Practical experience utilizing AI-driven development workflows, including automated code review tools, AI-assisted security vulnerability scanning, and intelligent CI/CD pipeline optimizations.
• Deep understanding of Microservices and event-driven architectures, Docker containers, and Kubernetes for both cloud and on-premises deployment models.
• Hands-on experience with modern data ecosystems and databases, including Apache Spark, Kafka, Pulsar, HDFS, Apache Airflow, Cassandra, MongoDB, Elasticsearch, and time-series databases.
• Proven track record working with a variety of AWS services.
• Excellent understanding of core protocols and security concepts such as HTTP, MQTT, SSL, Public Key Infrastructure (PKI), OAuth, and SAML.
• Strong working knowledge of design patterns and SOLID principles, coupled with a deep understanding of monitoring and logging tools.
• Strong understanding of prompt engineering principles to effectively collaborate with AI coding assistants, ensuring the generated code aligns with enterprise architecture and security standards.
• Exceptional presentation and communication skills, with the ability to persuade and clearly articulate technical ideas to diverse stakeholders.
• Hands-on experience integrating Large Language Models (LLMs) and AI APIs (e.g., OpenAI, Gemini, Claude) into enterprise-scale cloud applications.
• Familiarity with building Retrieval-Augmented Generation (RAG) pipelines, interacting with vector databases, or deploying machine learning models in a cloud-native ecosystem.