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Metro Hyderabad, generalist senior title, and broad AI/backend skillset increase applicant competition.
ML/backend skills are transferable, but life-sciences domain knowledge increases specialization moderately.
Explicit 7+ years requirement plus mandatory GenAI, AWS, and backend/ML expertise makes screening stringent.
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Design, develop, deploy, and maintain scalable AI/ML pipelines and software applications integrating ML models and LLMs into production.
Build and maintain backend services and APIs using Python, FastAPI, AWS services (Lambda, ECS, EC2) to enable secure, cloud-native AI architectures.
Collaborate cross-functionally to identify and extend AI/ML capabilities, troubleshoot production GenAI systems, and produce technical documentation.
7+ years of experience in software development, AI/ML solution design, backend engineering, or automation.
Strong proficiency in Python; experience with R programming is a plus.
Hands-on experience with Generative AI/LLM technologies (e.g., OpenAI, Gemini) and AWS cloud services including Lambda, API Gateway, SageMaker.
Functional knowledge of Life Sciences R&D domain and familiarity with Agile, DevOps, and CI/CD practices.
Experienced technical leader who can own end-to-end AI/ML production workflows and backend integration at scale.
Comfortable working in a cross-functional environment interfacing between product, engineering, and domain teams in Life Sciences.
Demonstrated expertise in cloud-native architectures and continuous optimization of AI-driven solutions in production.