AI/ML Architect

Job Title AI/ML Architect

Company: ToggleNow

Location: Hyderabad

Experience: 5–8 Years

Employment Type: Full-Time

Submit your application: https://ignite.togglenow.com/apply/REWW99ERAMJ6

About ToggleNow

ToggleNow is a global SAP solutions and digital transformation company helping enterprises accelerate business innovation through SAP, Cloud, AI, Data, and Enterprise Technology services.

We are looking for an experienced AI/ML Architect to lead the design and architecture of enterprise-grade Artificial Intelligence, Machine Learning, Generative AI, and Agentic AI solutions.

The ideal candidate will have strong hands-on experience combined with the ability to architect scalable AI platforms, lead technical teams, evaluate emerging AI technologies, and translate complex business requirements into production-ready AI solutions.

Key Responsibilities

• Design and architect scalable, secure, and enterprise-grade AI/ML and Generative AI solutions .
• Define end-to-end architecture for Machine Learning, Deep Learning, LLM, RAG, NLP, and Agentic AI applications.
• Architect and implement Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources.
• Design solutions using Large Language Models (LLMs) , including open-source and commercial models.
• Architect AI-powered chatbots, virtual assistants, recommendation systems, intelligent automation, and conversational AI solutions .
• Design and evaluate AI Agent and Multi-Agent architectures using appropriate frameworks and orchestration patterns.
• Define model selection, fine-tuning, evaluation, optimization, and deployment strategies.
• Establish scalable LLMOps/MLOps pipelines for model lifecycle management, monitoring, evaluation, and continuous improvement.
• Design AI solutions integrating structured and unstructured enterprise data.
• Architect APIs and microservices for integrating AI/ML capabilities with enterprise applications.
• Define cloud architecture and deployment strategies across AWS, Azure, and/or GCP .
• Ensure AI solutions meet requirements for security, scalability, performance, reliability, governance, and cost optimization .
• Lead technical discussions with product managers, engineering teams, business stakeholders, and customers.
• Conduct technical feasibility assessments, proof-of-concepts, and technology evaluations.
• Establish AI/ML engineering standards, reusable frameworks, design patterns, and best practices.
• Provide technical leadership and mentorship to AI/ML engineers and developers.
• Stay current with advancements in Generative AI, Agentic AI, Foundation Models, AI Agents, LLMOps, and emerging AI technologies .

Required Skills & Qualifications

• B.E./B.Tech/M.Tech in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related discipline.
• MCA/M.Sc. in Computer Science, Data Science, or AI may also be considered.
• 5–8 years of experience in AI/ML, Machine Learning Engineering, Data Science, AI Architecture, or related domains.
• Strong proficiency in Python and experience with production-grade software development.
• Strong understanding of Machine Learning and Deep Learning concepts and frameworks such as PyTorch, TensorFlow, and Scikit-learn.
• Extensive hands-on experience with Generative AI and Large Language Models (LLMs) .
• Strong experience designing and implementing RAG architectures .
• Experience with vector databases such as Pinecone, FAISS, ChromaDB, Weaviate, Milvus , or equivalent technologies.
• Strong knowledge of LangChain, LlamaIndex, OpenAI APIs , or similar GenAI frameworks.
• Strong understanding of NLP, Transformers, embeddings, semantic search, prompt engineering, and LLM evaluation .
• Experience designing and developing REST APIs and microservices using FastAPI, Flask, or similar frameworks.
• Strong understanding of AI/ML system architecture, distributed systems, scalability, and performance optimization .
• Experience with at least one major cloud platform: AWS, Azure, or GCP .
• Hands-on experience with Docker and Kubernetes and containerized application deployments.
• Experience with MLOps/LLMOps, CI/CD, model deployment, monitoring, and observability .
• Strong understanding of Git, software engineering pra…