Additional Expectations (Architect Level): Define AI roadmap and contribute to organizational AI strategy Establish reusable frameworks, accelerators, and best practices Drive cost optimization and performance efficiency at scale Ensure ethical AI and responsible AI implementation Key Requirements and Technology Experience: Must have skills: 11–13 years of experience in AI/ML, with significant experience in designing and deploying large-scale AI systems Data Modeling, Generative & Agentic AI, Machine Learning, Python, Embeddings & Vector Databases Proven experience in architecting enterprise-grade AI/ML platforms and solutions Technical Expertise: AI/ML & Advanced Analytics: Strong expertise in Machine Learning, Deep Learning, and statistical modeling Experience designing scalable ML systems and production pipelines Generative AI & Agentic AI: Deep expertise in LLMs (GPT, Claude, Llama, Gemini) and their enterprise applications Strong experience in RAG architectures, prompt engineering, context engineering, embeddings, and vector databases Hands-on experience with agentic frameworks (LangGraph, CrewAI, AutoGen) and multi agent orchestration Architecture & Engineering: Strong system design and architecture skills for distributed AI systems Expertise in Python, SQL, and software engineering best practices Experience with microservices, APIs, and scalable backend systems MLOps & Platform Engineering: Strong experience in MLOps practices including CI/CD, model versioning, monitoring, and governance Hands-on experience with tools such as MLflow, Vertex AI, Kubeflow, or similar Cloud & Data Platforms: Deep experience with cloud platforms, especially GCP (Vertex AI, BigQuery) and/or Databricks Strong understanding of data lakes, data warehouses, and real-time data processing Soft Skills & Mindset: Strategic Leadership: Ability to align AI initiatives with business goals and drive long-term technology vision Ownership & Accountability: Takes end-to-end ownership of architecture, delivery, and outcomes Influence & Communication: Strong ability to communicate complex technical concepts to senior stakeholders and executives Innovation Mindset: Continuously explores emerging AI trends and drives adoption of next-gen technologies Strong expertise in Machine Learning, Deep Learning, and statistical modeling Experience with Generative AI and Agentic AI frameworks Hands-on experience with LLMs such as GPT, Claude, Llama, and Gemini Strong knowledge of RAG architectures, prompt engineering, context engineering, embeddings, and vector databases Experience with agentic frameworks including LangGraph, CrewAI, and AutoGen Expertise in Python, SQL, and software engineering best practices Experience designing scalable AI/ML systems and production pipelines Strong understanding of distributed AI systems, microservices, and APIs Experience with MLOps tools such as MLflow, Vertex AI, and Kubeflow Deep experience with cloud platforms, especially GCP and Databricks Knowledge of data lakes, data warehouses, and real-time data processing Strong leadership, communication, and stakeholder management skills Experience driving enterprise AI strategy, governance, and responsible AI practices Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field Our client is a leading IT Services and IT Consulting Industry and we are currently interviewing to fill this and other similar fulltime positions. Key Responsibilities: Architect & Scale AI Solutions: Design end-to-end AI/ML architectures, including scalable, secure, and production-ready systems using Machine Learning, Deep Learning, and Large Language Models (LLMs).