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Principal MLOps Architect

Intellias

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Job Description:

We are seeking a highly experienced and hands-on Principal AI/ML Architect & Applied AI Lead to drive the design, development, and operationalization of enterprise-scale AI systems across research and production environments. This role combines deep technical expertise in Machine Learning, Generative AI, distributed data systems, and cloud-native architectures with strategic leadership capabilities. The ideal candidate will lead complex AI initiatives end-to-end — from experimentation and research to scalable deployment in global enterprise environments. The position requires a strong balance between: technical leadership, hands-on implementation, AI strategy, cross-functional collaboration, and mentoring of engineering and data science teams.

Job Responsibility:

  • Lead the design and implementation of AI/ML solutions across multiple business domains.
  • Drive enterprise adoption of Large Language Models (LLMs), Generative AI, NLP/NLU, and advanced analytics solutions.
  • Define AI architecture standards, MLOps best practices, and scalable deployment strategies.
  • Evaluate emerging AI technologies and identify opportunities for innovation and operational impact.
  • Translate research initiatives into production-ready AI solutions.
  • Architect scalable distributed data-processing systems capable of handling large-scale datasets and real-time pipelines.
  • Design and optimize cloud-native AI platforms using modern data engineering frameworks.
  • Lead cloud migration and modernization initiatives from on-premises environments to Azure and/or AWS.
  • Implement efficient data pipelines leveraging Spark, Delta Lake, Databricks, Kubernetes, and containerized environments.
  • Ensure reliability, scalability, observability, and cost-efficiency of AI infrastructure.
  • Design and implement enterprise-grade chatbot and conversational AI platforms.
  • Lead development of Retrieval-Augmented Generation (RAG), agentic workflows, and LLM orchestration systems.
  • Define governance, evaluation, and monitoring strategies for GenAI systems.
  • Collaborate with research teams to operationalize LLM-based applications securely and responsibly.
  • Lead cross-functional teams composed of data scientists, ML engineers, software engineers, and business stakeholders.
  • Mentor engineers and researchers in AI/ML best practices, architecture, and software engineering standards.
  • Coordinate global AI initiatives across distributed teams and multiple geographies.
  • Communicate technical concepts effectively to executive and non-technical audiences.
  • Support innovation programs and AI adoption strategies across the organization.

Requirements:

  • Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field
  • 10+ years of experience in AI/ML, data science, or distributed systems engineering.
  • Proven experience designing and deploying production-grade AI solutions at enterprise scale.
  • Strong background in both research and industrial AI environments.
  • Experience leading global or distributed technical teams.
  • Demonstrated success delivering AI transformation initiatives.
  • Large Language Models (LLMs)
  • Generative AI systems
  • NLP / NLU
  • Apache Spark
  • Databricks
  • Delta Lake
  • SQL / NoSQL databases
  • Distributed computing architectures
  • Streaming and batch processing pipelines
  • Azure and/or AWS
  • Docker
  • Kubernetes
  • CI/CD pipelines
  • Infrastructure-as-Code
  • MLOps frameworks
  • Python
  • Scala
  • Experience with AI governance and responsible AI practices.
  • Experience building AI platforms serving multiple teams or business units.
  • Experience optimizing cloud infrastructure and reducing operational costs.

Additional Information:

Job Posted:
May 17, 2026

Employment Type:
Fulltime
Work Type:
Remote work
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