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Project Role Description: Design and support implementation of AI-driven solutions within cloud-native architectures. Works with architects and delivery teams to translate AI use cases into scalable, production-ready systems leveraging GenAI, ML, and contemporary engineering practices. Must have Skills: AI/ML & GenAI (LLMs, RAG, Agents) Python-based development Cloud platforms (AWS / Azure / GCP) APIs and microservices. Good to Have Skills: MLOps and pipeline orchestration, Data engineering frameworks, DevOps and automation, Responsible AI practices Key Responsibilities: 1. Support design and implementation of AI/GenAI-enabled solutions 2. Develop and integrate AI components such as LLM-based services, RAG pipelines, and agents 3. Collaborate with architects to align AI solutions with enterprise architecture 4. Participate in solutioning activities for AI-led opportunities 5. Ensure adherence to best practices in scalability, reliability, and security 6. Contribute to reusable assets and accelerators. Technical Experience: Experience working with AI/ML frameworks and cloud AI services Understanding of microservices, APIs, and cloud-native architecture Exposure to CI/CD, containers, and modern development practices Familiarity with Agile delivery models. Professional Attributes: 12+ Years of experience Strong problem-solving mindset Good communication and collaboration skills Ability to work in fast-paced environments Continuous learning orientation. Educational Qualifications: Bachelors degree in Computer Science, Engineering, or related field. TBD Project Role Description: Design and support implementation of AI-driven solutions within cloud-native architectures. Works with architects and delivery teams to translate AI use cases into scalable, production-ready systems leveraging GenAI, ML, and contemporary engineering practices. Must have Skills: AI/ML & GenAI (LLMs, RAG, Agents) Python-based development Cloud platforms (AWS / Azure / GCP) APIs and microservices. Good to Have Skills: MLOps and pipeline orchestration, Data engineering frameworks, DevOps and automation, Responsible AI practices Key Responsibilities: 1. Support design and implementation of AI/GenAI-enabled solutions 2. Develop and integrate AI components such as LLM-based services, RAG pipelines, and agents 3. Collaborate with architects to align AI solutions with enterprise architecture 4. Participate in solutioning activities for AI-led opportunities 5. Ensure adherence to best practices in scalability, reliability, and security 6. Contribute to reusable assets and accelerators. Technical Experience: Experience working with AI/ML frameworks and cloud AI services Understanding of microservices, APIs, and cloud-native architecture Exposure to CI/CD, containers, and modern development practices Familiarity with Agile delivery models. Professional Attributes: 12+ Years of experience Strong problem-solving mindset Good communication and collaboration skills Ability to work in fast-paced environments Continuous learning orientation. Educational Qualifications: Bachelors degree in Computer Science, Engineering, or related field. TBD
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