Verified Job
IT / Software / Data Analyst
Technical Architect – AI & GenAI Specialization
IT / Software / Data Analyst
#746250
Remote / WFH
CareerNet Technologies Pvt Ltd · Bengaluru, Karnataka
Job Description
Job description
Key Skills: Artificial Intelligence, Generative AI, Large Language Models, Machine Learning, Cloud AI Services, Python, Azure, AWS, MLOps, TensorFlow
Good to Have Skills: PyTorch, Hugging Face, RAG, vector databases (FAISS, Pinecone, Weaviate), embeddings, Java, Go, GraphQL, REST APIs, event-driven architectures, Google Cloud, Kubernetes, serverless architecture, data engineering, data lakes, streaming analytics, prompt engineering, knowledge distillation, Docker containerization, AI governance frameworks, ethical AI principles, bias mitigation, stakeholder management and presentation skills.
Roles & Responsibilities:
• Define and implement AI architecture for enterprise applications with scalability and security considerations.
• Develop AI frameworks and models that integrate seamlessly with existing enterprise systems.
• Ensure AI solutions comply with data privacy regulations such as GDPR and CCPA.
• Architect AI-powered platforms that support Gen-AI and AI frameworks and models effectively.
• Execute the training, fine-tuning, and deployment of LLMs and ML models for production use.
• Optimize model performance using techniques such as prompt engineering and retrieval-augmented generation.
• Design and deploy AI solutions on Azure AI, AWS SageMaker, or Google Vertex AI platforms.
• Ensure AI applications are cloud-native, containerized with Docker and Kubernetes, and scalable.
• Work closely with engineering, data science, product, and business teams to align AI initiatives.
• Provide technical mentorship and guidance to AI engineers and developers within the organization.
• Implement AI governance frameworks for explainability, accountability, and security compliance.
Experience Required: 10-12 years of experience with strong hands-on expertise in LLMs, ML frameworks, and deep learning models. Experience with GenAI applications, enterprise software architectures, microservices, and cloud platforms required.
Education: B-Tech / M-Tech Computer Science preferred
Key Skills: Artificial Intelligence, Generative AI, Large Language Models, Machine Learning, Cloud AI Services, Python, Azure, AWS, MLOps, TensorFlow
Good to Have Skills: PyTorch, Hugging Face, RAG, vector databases (FAISS, Pinecone, Weaviate), embeddings, Java, Go, GraphQL, REST APIs, event-driven architectures, Google Cloud, Kubernetes, serverless architecture, data engineering, data lakes, streaming analytics, prompt engineering, knowledge distillation, Docker containerization, AI governance frameworks, ethical AI principles, bias mitigation, stakeholder management and presentation skills.
Roles & Responsibilities:
• Define and implement AI architecture for enterprise applications with scalability and security considerations.
• Develop AI frameworks and models that integrate seamlessly with existing enterprise systems.
• Ensure AI solutions comply with data privacy regulations such as GDPR and CCPA.
• Architect AI-powered platforms that support Gen-AI and AI frameworks and models effectively.
• Execute the training, fine-tuning, and deployment of LLMs and ML models for production use.
• Optimize model performance using techniques such as prompt engineering and retrieval-augmented generation.
• Design and deploy AI solutions on Azure AI, AWS SageMaker, or Google Vertex AI platforms.
• Ensure AI applications are cloud-native, containerized with Docker and Kubernetes, and scalable.
• Work closely with engineering, data science, product, and business teams to align AI initiatives.
• Provide technical mentorship and guidance to AI engineers and developers within the organization.
• Implement AI governance frameworks for explainability, accountability, and security compliance.
Experience Required: 10-12 years of experience with strong hands-on expertise in LLMs, ML frameworks, and deep learning models. Experience with GenAI applications, enterprise software architectures, microservices, and cloud platforms required.
Education: B-Tech / M-Tech Computer Science preferred
