Senior Architect - Artificial Intelligence & Machine Learning

VAYUZ Technologies; Bengaluru; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

VAYUZ Technologies is seeking an AI/ML Architect to define and drive the organization’s AI strategy. You will design scalable pipelines, evaluate LLM frameworks, and guide multi-disciplinary teams to translate requirements into technology roadmaps.

You will mentor engineers, lead PoCs for new AI tech, and ensure governance and privacy compliance across systems, while optimizing performance and cost.

Qualifications

• 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.
• Strong 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.

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.

Skills

AI/ML architecture

LLM ecosystems

Vector databases

Cloud architecture

MLOps tools

Python

Data engineering

Microservices/API design

AI governance

Containerization

Tools

Docker

Kubernetes

Helm

MLflow

Kubeflow

Weights & Biases

Job description

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 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
• Strong 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)