AI Architect

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