Senior Software Development Engineer - AI and Optimization
Hewlett Packard Enterprise (HPE) (company site, opens in a new tab)6–10 yrsBengaluruOn-siteDirect career pageEst. 30–45 LPA
Posted 10h ago
Reach people at Hewlett Packard Enterprise (HPE)
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 Hewlett Packard Enterprise (HPE) 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, development, and delivery of AI-enabled security software applications improving engineering productivity and security analysis.
- Drive end-to-end execution ensuring scalable, maintainable, secure solutions aligned with technical and business goals.
- Provide technical leadership across cross-functional teams, influencing technical direction and resolving complex challenges.
Minimum Requirements
- Bachelor's or Master's degree in Computer Science, Information Systems, or related field, or equivalent experience.
- 6-10 years of software engineering experience designing and delivering enterprise applications and platforms.
- Experience with MERN stack, Python, CI/CD tools (GitOps, Docker, Jenkins, GitHub Actions), and software architecture across multiple platforms.
- Experience with AI/ML technologies including large language models, MLOps, agentic AI concepts, and understanding of AI security and responsible AI principles.
Ideal Candidate Profile
- Experienced in transforming ambiguous problems into scalable, maintainable AI-based cybersecurity solutions with measurable impact.
- Strong technical depth with skills spanning software engineering fundamentals, architecture, AI experimentation, and production deployment.
- Comfortable providing technical leadership, mentoring engineers, influencing technical direction, and working cross-functionally in enterprise security environments.