Principal Architect- AI ,ML

Position Principal Architect AI/ML

Department: Engineering & Technology | Function: AI/ML Platform Engineering

Min Exp 12+ yrs

Max salary up to 40 lpa

Required Education & Certifications

• Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or a relatedtechnical field.
• Certifications in cloud platforms (AWS, Azure, GCP) or specialized AI/ML credentials are preferred

Responsibilities

AI/ML Architecture & Engineering

Hands-on Development & Technical Leadership

AI/ML & GenAI Solution Development

MLOps & Platform Engineering

Cloud & Distributed Systems

Data & Platform Readiness

Technical Mentorship & Collaboration

Work Experience

• 12+ years of experience in AI/ML, software engineering, or platform engineering roles.
• Proven experience designing and deploying AI/ML solutions in production environments.
• Strong hands-on expertise in Python, SQL, and distributed computing frameworks.
• Hands-on experience with ML libraries/frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience building end-to-end ML systems not just modelling.
• Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Azure ML, Vertex AI, Airflow).
• Hands-on experience with GenAI/LLMs (RAG, embeddings, fine-tuning, prompt engineering).
• Experience working with cloud platforms (AWS/Azure/GCP).

Key Skills & Competencies

Technical Skills

• Deep expertise in AI/ML architecture, distributed systems, and cloud-native engineering.
• Strong knowledge of system design, scalable architectures, data pipelines, and distributed

systems.

• Proficiency in Python, SQL, TensorFlow, PyTorch, and Scikit-learn.
• Experience with MLOps platforms and CI/CD-integrated ML workflows.
• Familiarity with vector databases, knowledge graphs, or multimodal AI systems is a plus.
• Exposure to real-time ML systems or streaming architectures is a plus.

• AI & Digital Competencies
• • Hands-on experience with GenAI and LLM-based solutions including RAG, embeddings, and
• fine-tuning.
• • Experience building AI platforms or internal ML frameworks.
• • Strong understanding of AI adoption, model lifecycle management, and intelligent
• automation.

• Leadership & Behavioural Competencies
• • Strong hands-on technical mindset with a passion for building scalable, production-grade
• systems.
• • Ability to operate as a player-coach architect and active contributor simultaneously.
• • Deep problem-solving skills with a focus on scalability and performance.
• • Strong collaboration and stakeholder management skills across engineering, product, and
• platform teams.
• • Continuous learning mindset, especially in emerging AI and GenAI technologies.

Please apply to this job here, we will call you once your profile is shortlisted.