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Tier-1 employer and metro mid-level GenAI role create moderate applicant competition.
Highly specialized GenAI skills limit cross-industry transferability.
Explicit 4–7 years and mandatory GenAI stack make filtering stringent.
Design, build, fine-tune, and deploy generative AI solutions using large language models (OpenAI, Anthropic, Mistral, LLaMA, Falcon) on cloud platforms (Azure, AWS, GCP).
Develop and optimize prompt engineering strategies and implement AI model pipelines using Python, PyTorch, Hugging Face Transformers, and orchestration frameworks like LangChain.
Collaborate with engineering and MLOps teams to integrate GenAI models via APIs and ensure scalability, robustness, and compliance in enterprise environments.
4 to 7 years of work experience in Generative AI or related fields.
Bachelor's degree in Technology (B.E/B.Tech) required; M.Tech or MCA preferred.
Strong expertise in Generative AI (LLMs, Transformers), Python, PyTorch, Hugging Face Transformers.
Experience with cloud AI platforms and deployment tools: Azure, AWS, GCP, LangChain, REST APIs (FastAPI, Flask), ML pipeline tools (MLflow, Weights & Biases), and CI/CD for ML (Azure ML, SageMaker).
Experienced in deploying scalable generative AI solutions within enterprise/cloud environments demonstrating proficiency in full model lifecycle from fine-tuning to production.
Skilled in orchestration of AI workflows and integration of GenAI capabilities via APIs, showing ability to collaborate closely with data engineering and MLOps teams.
Familiar with advanced AI tooling including prompt engineering, agentic AI frameworks, and observability/performance evaluation techniques relevant to GenAI applications.