What You’ll Do

- Design and develop medium-high complexity AI/ML-powered, cloud-native application features in accordance with business and technical requirements.
- Apply practical knowledge of AI/ML technologies to build enterprise-grade solutions using generative AI and large language models (LLMs).
- Develop, enhance, test, and maintain secure, scalable GenAI and cloud application components in alignment with established engineering standards and security policies.
- Deploy application code, monitor performance, and diagnose and resolve issues across application modules and deployment environments.
- Collaborate with software engineers, architects, technical contributors, technical writers, product stakeholders, and managers to review designs and share innovative technical ideas.
- Analyse technical and business requirements, identify root causes, and implement effective solutions for complex application, system administration, data-processing, and network-related issues.

What You’ll Bring
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a closely related quantitative discipline; a master’s degree is preferred.
- 3–5 years of professional software engineering experience,



including at least one year of hands-on experience developing enterprise applications using generative AI and LLM technologies.

Knowledge and Skills · Hands-on experience designing and developing enterprise applications powered by generative AI and large language models.

· Strong programming skills in Python, including experience with Pandas, scikit-learn, and NumPy; proficiency in Go (Golang) is an advantage.

· Solid understanding of database technologies, including graph databases, relational databases (SQL), and NoSQL databases.

· Experience with software design methodologies, cloud-native architectures, developer tooling, APIs, and managed services.

· Demonstrated experience designing, developing, and deploying cloud-native applications on AWS, Microsoft Azure, or Google Cloud Platform.

· Ability to learn recent technologies quickly, communicate clearly, and collaborate effectively within cross-functional and distributed teams.

· Working knowledge of DevOps practices, including continuous integration and continuous delivery/deployment (CI/CD), containerisation, and orchestration with Kubernetes.

📌 AI/ML Software Deveveloper (3+ years of experience) (Bangalore Urban)
🏢 HPE Aruba Networking
📍 Bangalore Urban