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Strong employer brand and Hyderabad metro increase competition but niche LLM specialization limits applicant pool.
ML/LLM and cloud deployment skills transfer across industries but require specialized model productionization experience.
Explicit 8+ years and 3+ lead experience plus mandatory LLM, Python, cloud, and DevOps skills.
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Lead the design, development, and deployment of AI/ML solutions including LLMs (e.g., Llama, GPT) and advanced NLP/NLU workflows, focusing on automation and scalable data processing pipelines.
Own architecture and delivery of Python-based APIs and microservices, implementing best practices for performance and scalability within a cloud environment (AWS preferred).
Provide technical leadership by mentoring engineers, conducting system design reviews, ensuring code quality, and managing incident resolution and production troubleshooting.
8+ years of software development experience, including 3+ years in senior or lead roles delivering ML/AI solutions in cloud environments.
Strong expertise in LLM prompt engineering, few-shot prompting, fine-tuning using frameworks such as Hugging Face, LangChain, and LangGraph.
Mastery of Python for API/microservice development and experience deploying AI/ML services on AWS (or Azure/GCP), including containers, serverless, and IaC.
Bachelor's degree in Engineering, Computer Science, or equivalent.
Experienced in end-to-end AI/ML system architecture and cloud deployment, particularly AWS, with practical skills in containerization, DevOps practices, and production-grade ML solution scaling.
Technically strong leader capable of guiding cross-team initiatives and mentoring engineers while enforcing high standards in design and code quality.
Comfortable working in product engineering settings with a focus on automation, scalability, and innovative AI/ML workflows leveraging open-source LLMs and cloud-native tooling.