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Intellias

Intellias is an AI-enabled product engineering and digital solutions partner. We help companies and professionals cut through complexity, focus on what matters, and deliver clear, measurable outcomes at scale.

We are looking for an experienced Principal AI/ML Architect & Applied AI Lead to drive the design, development, and implementation of enterprise-scale AI solutions. This is a hands-on leadership role combining advanced AI architecture, Generative AI expertise, technical strategy, and collaboration with global teams.

If you are passionate about building production-grade AI systems, LLM-powered solutions, and scalable AI platforms, this opportunity will allow you to shape the future of enterprise AI adoption.

Project Overview

We are working with global organizations to deliver advanced AI solutions that transform business processes and enable next-generation digital experiences.

As a Principal AI/ML Architect & Applied AI Lead, you will be responsible for leading AI initiatives from research and experimentation through production deployment. You will design scalable AI architectures, establish engineering standards, guide technical decisions, and collaborate with business and technology stakeholders.

This role requires a combination of:

  • hands-on AI engineering expertise,

  • enterprise architecture experience,

  • strategic thinking,

  • technical leadership,

  • mentoring and consulting skills.

Responsibilities

  • Design and implement enterprise-scale AI/ML solutions across multiple business domains.

  • Lead architecture and development of production-grade LLM and agentic AI systems.

  • Build and evolve Generative AI solutions including:

    • Retrieval-Augmented Generation (RAG),

    • AI agents,

    • tool/function calling,

    • multi-agent orchestration.

  • Define AI architecture standards, MLOps practices, governance models, and deployment strategies.

  • Design scalable AI platforms supporting model portability and flexible LLM integration.

  • Work with cloud AI platforms such as AWS Bedrock or equivalent solutions.

  • Establish AI evaluation, monitoring, observability, and quality assurance strategies.

  • Design secure AI platforms with appropriate identity management, access control, and auditability.

  • Support AI platform modernization and migration initiatives.

  • Integrate AI platforms with enterprise data ecosystems and lakehouse environments.

  • Ensure AI infrastructure reliability, scalability, performance, and cost efficiency.

  • Collaborate with data scientists, ML engineers, software engineers, and business stakeholders.

  • Provide technical leadership, mentoring, and guidance to engineering teams.

  • Communicate complex technical concepts to both technical and executive audiences.

Requirements

  • 5+ years of experience in AI/ML, data science, or distributed systems engineering.

  • Proven experience designing and delivering production-grade AI solutions at enterprise scale.

  • Hands-on experience with:

    • LLM systems,

    • AI agents,

    • agentic RAG,

    • tool/function calling,

    • multi-agent architectures.

  • Experience with cloud AI platforms (AWS Bedrock/AgentCore or similar).

  • Experience with LLM evaluation, monitoring, observability, and production tracing.

  • Understanding of AI security concepts:

    • enterprise identity,

    • OAuth/Entra,

    • role-based access control,

    • permission-aware retrieval,

    • auditability.

  • Strong Python skills.

  • Experience with SQL and NoSQL databases.

  • Knowledge of modern cloud-native technologies:

    • Docker,

    • Kubernetes,

    • CI/CD pipelines,

    • Infrastructure as Code,

    • MLOps frameworks.

  • Experience working with distributed/global teams.

  • Ability to work directly with clients and advise stakeholders on AI strategy and architecture.

  • Experience using AI coding assistants (e.g. Claude Code, Copilot) and promoting AI-assisted engineering practices.

  • English proficiency at B2/C1 level.

Nice to have

  • Experience with Databricks / Unity Catalog or enterprise lakehouse environments.

  • Experience migrating AI platforms or modernizing existing AI ecosystems.

  • Experience defining architecture governance practices and technical documentation standards.

  • Background in consulting or technology advisory roles.

Why join?

  • Work on cutting-edge enterprise AI initiatives.

  • Influence AI strategy and architecture decisions for global organizations.

  • Build production-scale Generative AI and agentic systems.

  • Collaborate with experienced AI engineers, architects, and technology leaders worldwide.

  • Have a real impact on how organizations adopt and scale AI solutions.

Join us and help shape the next generation of enterprise AI platforms.

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