Key Responsibilities

Define and drive the overall AI/ML architecture strategy across the organization
Design scalable, resilient, and secure AI pipelines and platforms
Lead the evaluation and adoption of AI frameworks, LLM APIs, and vector databases
Collaborate with Product, Engineering, and Business leaders to translate requirements into technical roadmaps
Establish best practices for model lifecycle management, MLOps, and responsible AI
Conduct architecture reviews, code reviews, and technical design sessions
Mentor senior engineers and provide technical leadership across squads
Drive proof-of-concepts (PoCs) for emerging AI technologies and recommend adoption
Ensure compliance with data privacy regulations (GDPR, DPDPA) in AI systems
Own non-functional requirements: scalability, latency, availability, and cost optimization

Key Skills & Requirements

Deep expertise in AI/ML architecture patterns: RAG, agentic AI, multi-model orchestration
Proficiency with LLM ecosystems: OpenAI, Anthropic Claude, Google Gemini, open-source LLMs (Llama, Mistral)




Strong knowledge of vector databases: Pinecone, Weaviate, pgvector, ChromaDB
Cloud architecture expertise: AWS, GCP, or Azure (AI/ML services SageMaker, Vertex AI, Azure OpenAI)
Experience with MLOps tools: MLflow, Kubeflow, Weights & Biases
Proficiency in Python for AI/ML; working knowledge of Node.js or Java for backend integration
Knowledge of data engineering: Spark, Kafka, dbt, Airflow
Robust understanding of microservices, API design, and event-driven architecture
Familiarity with AI governance, model evaluation frameworks, and prompt engineering
Experience with containerization: Docker, Kubernetes, Helm

Nice To Have

Experience with agentic frameworks: LangChain, LlamaIndex, AutoGen, CrewAI
Published research or open-source contributions in AI/ML
Exposure to multi-modal AI (vision, voice, video) systems
Prior startup or product-led company experience

(ref:hirist.tech)

📌 Senior Architect (Bengaluru)
🏢 VAYUZ Technologies
📍 Bengaluru