Role : Principal AI Architect

We are seeking a highly experienced and visionary Principal AI Architect to design, lead, and implement enterprise-scale AI, Machine Learning, and Generative AI solutions. The ideal candidate will have strong expertise in building scalable AI platforms using Databricks, Snowflake, and cloud-native ecosystems, along with hands-on experience in Feature Engineering, RAG, LLMs, and Agentic AI architectures.

Key Responsibilities :

AI/ML and GenAI Architecture :

- Define end-to-end architecture for AI/ML and Generative AI systems.

- Design scalable Lakehouse-based AI platforms using Databricks and Snowflake.

- Architect solutions supporting batch and real-time inference workloads.

- Design enterprise-grade LLM, RAG, and Agentic AI applications.

- Establish architectural standards, best practices, and reusable AI frameworks.

RAG, LLM and Agentic AI :

- Design and implement Retrieval-Augmented Generation architectures using vector databases and knowledge pipelines.

- Architect intelligent AI agents for automation, orchestration, and decision-making workflows.

- Evaluate and integrate LLMs such as OpenAI and LLaMA.

- Optimize prompt engineering, embeddings, context management, scalability, accuracy, and cost.

- Develop enterprise-ready GenAI solutions.

Data and Feature Engineering :

- Design robust data pipelines for structured and unstructured data.

- Lead feature engineering strategies for ML and AI models.

- Collaborate with Data Engineering teams to build high-performance data ingestion and transformation pipelines.

- Implement data governance, lineage, and data quality frameworks.

Cloud and AI Platform Architecture :

- Architect AI solutions on AWS, Azure, or GCP.

- Design cloud-native and microservices-based AI systems.

- Leverage Docker and Kubernetes for scalable AI deployments.

- Implement MLOps and LLMOps best practices for CI/CD, monitoring, and lifecycle management.

Technical Leadership and Innovation :

- Conduct Proof of Concepts to validate architectural approaches and design decisions.

- Analyze existing product architecture and recommend AI-driven enhancements.

- Provide technical leadership and mentorship to AI, Data Science, and Engineering teams.

- Identify emerging AI and GenAI trends and enterprise adoption opportunities.

- Collaborate with product managers, stakeholders, and business leaders to translate business requirements into AI solutions.

Governance, Security and Compliance :

- Define AI governance frameworks including model monitoring and responsible AI practices.

- Ensure compliance with data privacy and enterprise security standards.

- Implement observability, model performance tracking, and risk mitigation strategies.

Required Skills and Qualifications :

- 12+ years of experience in AI/ML Architecture, Data Engineering, Advanced Analytics, or related areas.

- Strong expertise in Generative AI, LLMs, RAG, and Agentic AI architectures.

- Hands-on experience with Databricks, Snowflake, and Lakehouse architecture.

- Strong programming skills in Python and PySpark.

- Experience with TensorFlow, PyTorch, and Scikit-learn.

- Experience with Vector Databases such as FAISS, Pinecone, or Weaviate.

- Knowledge of MLOps and LLMOps tools such as MLflow, Kubeflow, or Azure ML.

- Experience designing real-time and batch AI pipelines.

- Strong understanding of Feature Engineering and model lifecycle management.

- Experience with REST APIs, microservices, and scalable system design.

- Strong knowledge of cloud platforms such as AWS, Azure, or GCP.

- Experience with Docker and Kubernetes is preferred.