Principal Architect AI/ML

Minimum Years of Experience:

Key Responsibilities & Required Qualifications

Candidate should be ready to work from the client place (Hyderabad)On site

• Masters degree in Artificial Intelligence, Computer Science, or related field (PhD preferred).
• 12+ years in AI/ML architecture, cloud infrastructure design, and full lifecycle solution delivery.
• Proven track record designing and deploying scalable, production-grade AI systems on AWS, Azure, and GCP.
• Strong expertise in ML model development, fine-tuning, and deployment with TensorFlow, PyTorch, Hugging Face, and LangChain.
• Deep hands-on experience with NLP, LLMs, RAG pipelines, and generative AI applications.
• Lead architectural decisions for hybrid cloud environments, including container orchestration (Kubernetes, Docker Swarm), CI/CD pipelines (Jenkins, Git, Terraform), and observability (Grafana, Prometheus, ELK).
• Mentor cross-functional teams in data science, DevOps, and software engineering to deliver end-to-end AI/ML solutions.
• Collaborate with business leaders to translate complex business needs into AI-driven architectures and platforms.
• Drive the adoption of best practices in MLOps, security, scalability, and model monitoring.
• Published research, open-source contributions, or conference presentations

Must-Have Skills

• AI Architecture: Design and implement scalable architectures for ML, deep learning, and GenAI workloads.
• Cloud & DevOps: Expert in AWS, Azure, GCP, Terraform, Jenkins, Docker, Kubernetes, and CI/CD automation.
• Advanced ML & NLP: Proficiency in CNNs, RNNs, LSTMs, GANs, Transformers, tokenization, and NER.
• Data Engineering: Build robust data pipelines, optimize data flow, and integrate data lakes and warehouses.
• RAG & LLM Deployment: Experience with retrieval-augmented generation pipelines, Vertex AI, Bedrock, and fine-tuning workflows.
• Monitoring & Observability: Design monitoring solutions using Grafana, CloudWatch, New Relic, and ELK.
• Stakeholder Communication: Ability to present complex architectures and trade-offs to executive and technical teams.