AI Architect

Elabs Infotech; Hyderabad; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

Elabs Infotech is seeking an AI Architect / AI Platform Architect to design, develop, and operate large-scale distributed AI systems in production. You will build reusable platform capabilities and reference architectures adopted across teams, focusing on reliability, security, and scalable AI capabilities.

The role emphasizes defining enterprise patterns for AI/GenAI platforms, APIs, and evaluation frameworks, with a strong emphasis on observability, telemetry, and production readiness.

Qualifications

• 10+ years of experience designing, developing, and operating large-scale distributed AI systems in production.
• 3+ years in AI Platform, Architecture, Principal Engineer, Lead Engineer, or Architect roles preferred.
• Strong experience with enterprise-scale AI/ML or GenAI platforms.

Responsibilities

• Define and drive architecture for enterprise-scale AI and GenAI platforms.
• Design reusable APIs, services, frameworks, templates, and platform components.
• Establish scalable patterns for AI application development and deployment.
• Design distributed AI systems with strong reliability, security, scalability, and performance characteristics.
• Develop AI quality, evaluation, monitoring, and telemetry foundations.
• Define and implement production-readiness and operational standards for AI workloads.
• Establish reusable reference implementations and accelerators to drive AI adoption across teams.
• Design enterprise patterns for AI/Agent/Tool registries, private registries, RAG and grounding, retrieval and memory, context management and budgeting, production hardening.

Skills

AI Platform Architecture & Distributed

AI Quality & Evaluation

AI Telemetry & Monitoring

Job description

We are looking for a highly experienced AI Architect / AI Platform Architect to design, develop, and operate large-scale, distributed AI systems in production. The ideal candidate will have strong expertise in AI platform architecture, distributed systems, API design, reliability engineering, AI quality/evaluation, and AI observability.

The role will focus on building reusable AI platform capabilities and reference architectures that can be adopted by multiple teams across an enterprise, rather than developing one-off AI applications.

Experience

• 10+ years of experience designing, developing, and operating large-scale distributed AI systems in production.
• 3+ years of experience in AI Platform, Architecture, Principal Engineer, Lead Engineer, or Architect roles preferred.
• Strong experience working with enterprise-scale AI/ML or GenAI platforms.

Top 3 Must-Have Skills

1. AI Platform Architecture & Distributed Systems
   • Design scalable AI platforms and reusable components.
   • Strong understanding of API design, distributed systems, scalability, availability, and reliability engineering.
   • Experience building platform capabilities consumed by multiple engineering teams.
2. AI Quality & Evaluation
   • Experience implementing AI/ML/GenAI quality and evaluation practices.
   • Ability to define evaluation frameworks, quality metrics, validation approaches, and production-quality standards for AI systems.
3. AI Telemetry & Monitoring
   • Experience establishing AI observability, telemetry, monitoring, and operational foundations.
   • Strong understanding of production reliability, performance monitoring, troubleshooting, and operational readiness of AI systems.

Key Responsibilities

• Define and drive architecture for enterprise-scale AI and GenAI platforms.
• Design reusable APIs, services, frameworks, templates, and platform components.
• Establish scalable patterns for AI application development and deployment.
• Design distributed AI systems with strong reliability, security, scalability, and performance characteristics.
• Develop AI quality, evaluation, monitoring, and telemetry foundations.
• Define and implement production-readiness and operational standards for AI workloads.
• Establish reusable reference implementations and accelerators to drive AI adoption across teams.
• Design enterprise patterns for:
  • AI/Agent/Tool registries
  • Private registries
  • RAG and grounding
  • Retrieval and memory
  • Context management and budgeting
  • Production hardening
• Partner with engineering, data science, cloud, security, and product teams to establish enterprise AI architecture standards.
• Evaluate emerging AI/GenAI technologies and determine their applicability to enterprise platforms.
• Mentor senior engineers and architects and influence technical direction across teams.

Preferred Technical Experience

• Generative AI and Large Language Models such as:
  • OpenAI / GPT
  • Google Gemini
  • Meta Llama