Develop PoCs, prototypes, and MVPs to validate innovative cloud and AI use cases and accelerate adoption.
Collaborate with business stakeholders, architects, product teams, developers, and external technology partners.
Evaluate emerging technologies and assess their applicability, maturity, risks, and business value.
Ensure solutions address key aspects such as security, scalability, data privacy, performance, maintainability, and cost optimization.
Create reusable accelerators, frameworks, patterns, and knowledge assets to enable adoption across projects and teams.
Contribute to technology communities, competency development, mentoring, and knowledge-sharing initiatives.
Support customers and internal stakeholders in defining cloud and AI roadmaps and transformation strategies.
Core Technical Skills
Cloud
Strong understanding of cloud concepts, cloud-native architecture, and services.
Experience with one or more major cloud platforms such as Microsoft Azure, AWS, or Google Cloud.
Understanding of containers, APIs, microservices, serverless technologies, and cloud security.
AI / GenAI
Understanding of Generative AI, LLMs, prompt engineering, RAG, AI agents, embeddings, and vector databases.
Experience developing or integrating AI-powered applications and services.
Understanding of responsible AI, data privacy, security, and AI governance.
Engineering
Programming experience in technologies such as Python, Java, JavaScript/TypeScript or ABAP.
Experience with REST APIs, event-driven architecture, Git, CI/CD, and DevOps practices.
Understanding of databases, data platforms, and data integration.
Consulting & Leadership Competencies
Strong problem-solving and analytical thinking with the ability to move from problem identification to solution shaping.
Strong stakeholder management and communication skills.
Ability to translate complex technology concepts into business outcomes and value propositions.
Customer-centric mindset with strong consulting and influencing skills.
Ability to work effectively in cross-functional and distributed teams.
Curiosity and continuous learning mindset toward emerging cloud and AI technologies.
Ability to take end-to-end ownership and drive solutions from ideation ? PoC ? MVP ? production adoption.
Experience & Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
Typically 14+ years of experience in IT consulting, cloud engineering, solution architecture, enterprise applications, or digital transformation.
Demonstrated experience delivering cloud-based or AI-enabled solutions.
Experience working with enterprise customers and multiple stakeholders.
Cloud certification such as Azure, AWS, or Google Cloud is desirable.
SAP BTP / SAP AI / relevant AI certifications are an advantage.
BE, BTech,MCA
14 - 17 Years
