AI Architect

Actively Reviewing the Applications

Dextara Datamatics

India, Telangana, Hyderabad Full-Time On-site

Posted 2 weeks ago • Apply by June 15, 2026

Job Description

Job purpose

The AI Architect will lead design and delivery of AI solutions, with a strong focus on Generative AI, large language models (LLMs), AI agents, and core machine learning. The role combines architecture, hands-on prototyping, and close collaboration with business and engineering teams to turn AI opportunities into scalable, production-grade solutions.

Roles and Responsibilities

Define AI/ML architecture and standards, and guide teams on best practices across the AI portfolio.
Design end-to-end AI solutions, including agentic workflows, RAG systems, and ML models, that integrate with existing enterprise platforms.
Lead technical design reviews, PoCs, and reference implementations for AI agents, LLM use cases, and MLOps pipelines.
Collaborate with product, data, and engineering teams to translate business requirements into AI solution designs and roadmaps.
Support presales/RFPs with solution architectures, effort estimates, and implementation plans when required.
Mentor engineers and data scientists on AI architecture, coding standards, and operationalization of models.

Required experience

10+ years in data/AI/ML, including significant experience designing and deploying enterprise AI solutions.
Proven experience with LLMs and Generative AI (RAG, fine-tuning, prompt design) and at least one major cloud AI platform (AWS, Azure, or GCP).
Hands-on background in machine learning or deep learning using frameworks such as PyTorch or TensorFlow.
Strong understanding of MLOps concepts (model lifecycle, deployment, monitoring) and modern data platforms.

Core skills

AI agents and agentic workflows (tool use, orchestration, and integration with APIs and enterprise systems).
LLM and RAG architecture, vector databases, and evaluation of model quality and reliability.
Cloud-native design, microservices, and containerization (e.g., Docker/Kubernetes) for AI workloads.
Strong Python skills and familiarity with common AI/ML libraries and data engineering tools.