Generative Ai Engineer

2 hours ago

Bhavnagar, India Whatjobs IN C2 Full time

Position: Gen AI Engineer Location: Bangalore (Hybrid) Experience: Minimum 8 years (Total & Relevant) Mandatory Interview Mode: Face to Face We are seeking an experienced leader to design, build, and deploy scalable, ethical Generative AI solutions across the enterprise, ensuring alignment with business goals. Key Areas of Focus: 1. GenAI Expertise & Development: Design, develop, and deploy GenAI solutions for business use cases (content generation, summarization, intelligent assistants). Must have hands-on experience with GenAI platforms such as ChatGPT, Copilot, Azure OpenAI, Hugging Face Transformers , etc. Apply prompt engineering, model fine-tuning , and evaluation techniques to improve GenAI outputs. Integrate GenAI capabilities into enterprise applications and workflows. 2. Python, Data Science, and ML: Develop and maintain AI/ML models using Python and libraries (pandas, NumPy, scikit-learn, TensorFlow, PyTorch, LangChain ). Perform data analysis, feature engineering, and model validation. Build data pipelines and automate processing for scalable AI solutions. 3. Cloud Deployment & MLOps: Deploy and manage GenAI and ML solutions on major cloud platforms (Azure, AWS, or GCP ). Utilize cloud-native services (e.G., Azure Machine Learning, AWS SageMaker, GCP Vertex AI). Implement CI/CD, Docker, and Kubernetes to ensure scalability, security, and compliance in production environments. 4. Business Alignment & Agile Collaboration: Translate business requirements into technical specifications for GenAI solutions. Align AI initiatives with business strategy and KPIs. Work effectively within Agile teams , collaborating with Product Owners, Developers, and Data Scientists. 5. Risk, Compliance, and Ethics: Ensure GenAI solutions adhere to data privacy, security, and ethical standards (e.G., GDPR, AI ethics). Maintain transparency and explainability in AI models and outputs. Mandatory Skills Proven experience with Generative AI platforms and Large Language Models (LLMs). Strong proficiency in Python for AI/ML development. Solid understanding of data science principles and the end-to-end model lifecycle. Experience with cloud platforms (Azure, AWS, or GCP) and deploying AI solutions in production. Familiarity with Agile methodologies and excellent communication/stakeholder engagement skills .

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