Principal Software Engineer, Cloud Architecture

Principals

• Design, implement, test and release end-to-end workflows for our AI security product.
• Work across multiple agent platforms like AWS Bedrock, Google AgentSpace, Salesforce AgentForce, building foundational solutions using cloud, SAAS, and AI design patterns and technologies.
• Use AI and Agents to secure AI, using CUA agents, various LLM’s, agentic frameworks like ADK, Langchain among others.
• Design and develop secure, scalable, multi-tenant software solutions that run seamlessly across major cloud platforms like AWS and Azure.
• Act as a technical expert and thought leader, influencing product direction and engineering best practices.
• Drive continuous improvement in engineering processes, tooling, and operational reliability.
• Collaborate with internal teams to produce software design and architecture.
• Test and deploy applications and systems.
• Revise, update, refactor and debug code.
• Develop documentation throughout the software development life cycle.
• Serve as an expert on applications and provide technical support.
• Follow the true agile principles.

Qualifications

• 1+ year of experience as a Principal Software Engineer at a SaaS company.
• Expert-level ability utilizing technologies such as Java, Spring Framework, REST, and Microservices.
• Familiar with AI tools and curious about MCP, A2A, Agentic frameworks.
• Have a continuous learning mindset and not hesitate to venture into unchartered territory.
• Ability to perform research and go deep into platforms is a strong plus.
• Strong Experience as a Java Engineer developing applications based on Security principles, cloud platforms (AWS, Azure, or Google Cloud) and Containerization (Docker, Kubernetes).
• Deep understanding of data structures, algorithms, and design patterns.
• Hands-on experience with SQL, ElasticSearch, Redis, CI/CD, AWS Glue, Kafka.
• Experience in increasing levels of responsibility managing application development, solution architecture, design and delivery, and process improvement.
• Experience with unit, functional and system integration testing.
• Extensive understanding of working in an agile environment utilizing Scrum and Kanban.
• Experience with Git (GitHub/GitLab), automatic deployments, continuous integration.
• Experience using IntelliJ or Eclipse/My Eclipse IDE, writing Junit test cases, working with Maven/Ant.
• Experience with AI development tools in SDLC such as Amazon Q, Github Copilot, Cursor, and similar productivity assistants.
• Familiarity with various architectural patterns (e.g., event-driven, microservices, serverless) and their trade-offs.

What You Bring

Complete security & privacy literacy and awareness training during onboarding and annually thereafter.

Review (initially and annually thereafter), understand, and adhere to Information Security/Privacy Policies and Procedures such as (but not limited to): Data Classification, Retention & Handling Policy, Incident Response Policy/Procedures, Business Continuity/Disaster Recovery Policy/Procedures, Mobile Device Policy, Account Management Policy, Access Control Policy, Personnel Security Policy, Privacy Policy.