Job
Description
Key Responsibilities Architecture Development Define and implement AI architecture for enterprise applications. Develop AI frameworks and models that integrate with existing enterprise systems . Ensure AI solutions are scalable, secure, and compliant with data privacy regulations (GDPR, CCPA, etc.) . Technical Leadership & Innovation Architect AI-powered platforms that support Gen-AI & AI frameworks and models. Stay ahead of AI advancements and drive innovation in AI-driven automation, personalization, and optimization . AI Model Development & Optimization Execute the training, fine-tuning, and deployment of LLMs and ML models. Optimize model performance using techniques such as prompt engineering, retrieval-augmented generation (RAG), and knowledge distillation . Implement MLOps and AIOps best practices for continuous model monitoring and improvement. Cloud & Infrastructure Integration Design and deploy AI solutions on Azure AI, AWS SageMaker, Google Vertex AI, or OpenAI services . Ensure AI applications are cloud-native, containerized (Docker, Kubernetes), and scalable . Implement data pipelines, feature stores, and vector databases for efficient AI processing. Cross-Functional Collaboration Work closely with engineering, data science, product, and business teams to align AI initiatives with company goals. Provide technical mentorship and guidance to AI engineers and developers. Communicate AI strategy and roadmaps to senior leadership and stakeholders. Security, Compliance & Responsible AI Ensure AI solutions adhere to ethical AI principles, bias mitigation, and fairness . Implement AI governance frameworks for explainability, accountability, and security. Address risks related to AI hallucinations, adversarial attacks, and regulatory compliance . Qualifications Educational qualification: B-Tech / M-Tech Computer Science preferred Experience : 10+ Years Mandatory/requires Skills : Core AI & GenAI Expertise Strong hands-on experience with LLMs (GPT, Llama, Claude, etc.), ML frameworks (TensorFlow, PyTorch, Hugging Face), and deep learning models . Expertise in GenAI applications, including chatbots, code generation, multimodal AI, and synthetic data generation . Experience with RAG, vector databases (FAISS, Pinecone, Weaviate), and embeddings . Proficiency in AI-driven knowledge management, summarization, and automation . Software Architecture & Engineering Strong understanding of enterprise software architectures, microservices, APIs, and distributed computing . Hands-on experience with Python, Java, Go, or other relevant languages . Familiarity with GraphQL, REST APIs, and event-driven architectures . Experience with MLOps pipelines, CI/CD for AI, and automated AI workflows . Cloud & DevOps Expertise in deploying AI models on Azure, AWS, or Google Cloud . Experience with serverless AI architecture, Kubernetes, and cloud-native AI . Knowledge of data engineering, data lakes, and streaming analytics for AI . Preferred Skills : Leadership & Communication Ability to translate complex AI concepts into business-friendly insights. Strong stakeholder management, presentation, and decision-making skills.
