Principal AI Architect
Atharva IT · Bengaluru, Karnataka, India
Apply & track with Apply EdgeThe 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 (Retrieval-Augmented Generation), and Agentic AI architectures.This role involves understanding existing product architecture, defining future AI roadmaps, and delivering proof-of-concepts (POCs) to validate design decisions and innovation strategies. You will work closely with cross-functional teams to build intelligent, scalable, secure, and production-grade AI systems.Key Responsibilities1. AI, ML & Generative AI ArchitectureDefine end-to-end architecture for AI/ML and Generative AI systems including data ingestion, feature engineering, model training, deployment, monitoring, and governanceDesign and implement scalable Lakehouse-based AI platforms using Databricks and SnowflakeArchitect solutions supporting both batch and real-time inference workloadsLead the design of enterprise-grade GenAI applications using LLMs, RAG pipelines, and Agentic AI frameworksEstablish architectural standards, best practices, and reusable AI frameworks2. RAG, LLM & Agentic AI SolutionsDesign and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and knowledge pipelinesArchitect intelligent AI agents for automation, orchestration, and decision-making workflowsEvaluate and integrate LLMs (OpenAI, LLaMA, etc.) for enterprise use casesOptimize prompt engineering, embeddings, and context management strategiesEnsure scalability, accuracy, and cost optimization in GenAI deployments3. Data & Feature EngineeringDesign robust data pipelines for structured and unstructured dataLead feature engineering strategies for ML and AI modelsCollaborate with Data Engineering teams to build high-performance data ingestion and transformation pipelinesImplement data governance, lineage, and quality frameworks4. Cloud & Platform ArchitectureArchitect AI solutions on cloud platforms such as AWS, Azure, or GCPDesign cloud-native, microservices-based AI systemsLeverage containerization and orchestration tools (Docker, Kubernetes) for scalable deploymentsImplement MLOps and LLMOps best practices for CI/CD, monitoring, and lifecycle management5. POCs, Innovation & Technical LeadershipConduct Proof of Concepts (POCs) to validate architectural approaches and design considerationsAnalyze current product architecture and recommend AI-driven enhancementsProvide technical leadership and mentorship to AI, Data Science, and Engineering teamsDrive innovation by identifying emerging AI/GenAI trends and enterprise adoption opportunitiesCollaborate with stakeholders, product managers, and business leaders to translate business needs into AI solutions6. Governance, Security & ComplianceDefine AI governance frameworks including model monitoring, explainability, and ethical AI practicesEnsure compliance with data privacy and enterprise security standardsImplement observability, model performance tracking, and risk mitigation strategiesRequired Skills & Qualifications12+ years of experience in AI/ML architecture, Data Engineering, or Advanced AnalyticsStrong expertise in Generative AI, LLMs, RAG, and Agentic AI architecturesHands-on experience with Databricks, Snowflake, and Lakehouse architectureProficiency in Python, PySpark, and AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn)Experience with Vector Databases (FAISS, Pinecone, Weaviate, etc.)Strong knowledge of MLOps/LLMOps tools such as MLflow, Kubeflow, or Azure MLExperience designing real-time and batch AI pipelinesDeep understanding of Feature Engineering and model lifecycle managementStrong experience with REST APIs, microservices, and scalable system design