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Strong employer brand, metro location, and broad AI/cloud skillset requirements increase candidate competition.
Specialized generative AI and LLM deployment skills limit cross-industry transferability.
Requires specific LLM, LangChain, vector DB, AWS, and ML deployment skills, raising filtering strictness.
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Lead design and implement complex AI-driven architectures, including LLM applications, prototypes, and production-ready solutions.
Manage medium to large-scale projects involving system components and cross-functional collaboration for seamless AI integration.
Mentor software engineers and drive application development to deliver measurable business value using advanced AI/ML technologies.
Work Experience Required: Not explicitly mentioned in the JD
Proficiency with LLM APIs (OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI) and frameworks like LangChain or similar.
Hands-on experience with AWS services including ECS, KDA, Kinesis, OpenSearch, DynamoDB, CloudWatch, Lambda, API Gateway, and SageMaker Studio.
Knowledge of Generative AI techniques, ML model deployment, NLP, and strong programming skills in Python and ML frameworks (TensorFlow, PyTorch, Keras).
Experienced in building and deploying AI/ML solutions involving large language models and vector database technologies in cloud environments (AWS, Azure).
Strong ability to lead complex projects with hands-on technical expertise and to bridge architecture with product delivery.
Demonstrated capability to translate innovative AI research into practical POC/pilot and production deployments with a focus on scalability and business impact.