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.

· Solid 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 new 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) (Karnataka)
🏢 HPE Aruba Networking
📍 Karnataka