Enterprise Data & AI Orchestration Architect
Salary$50/hr
LocationUruguay
Work moderemote
Typecontract
SeniorityLead
DepartmentWorkana (inhouse)
Company size501–1,000 people
PostedMay 6, 2026 · 5mo ago
Verified live21h ago
At a glanceSummarised by Seekless from the posting.
Advanced academic background in Computer Science, Machine Learning, Data Engineering, or a related field. PhD preferred; Master's degree also considered.
Deep hands-on experience building enterprise data platforms in complex, multi-system environments.
Strong experience with production AI/ML systems, MLOps, observability, evaluation frameworks, and AI governance.
Experience with agentic or GenAI orchestration frameworks such as LangChain, LlamaIndex, AutoGen, Semantic Kernel, or similar.
Ability to advise senior technical stakeholders, including CTOs, CDOs, data leaders, and platform engineering teams.
Strong architectural judgment and ability to identify what is technically realistic, scalable, and enterprise-ready.
Strong English communication skills.
Experience with Microsoft AI ecosystem tools such as Azure AI, Azure OpenAI, Copilot, or Copilot Studio.
Experience with Snowflake, Databricks, MLflow, Kubernetes, Airflow, dbt, or similar enterprise data/AI tooling.
Skills
LangChain
LlamaIndex
AutoGen
Semantic Kernel
Azure AI
Azure OpenAI
Copilot
Copilot Studio
Snowflake
Databricks
MLflow
Kubernetes
Airflow
dbt
Benefits
Remote stipend
About the role
Xenon7 is looking for a Fractional Enterprise Data & AI Orchestration Architect to support senior-level client conversations, technical discovery, and architecture validation for enterprise AI initiatives.
This is a part-time advisory role, ideal for someone with deep experience designing enterprise data platforms, AI orchestration layers, MLOps practices, and production-grade GenAI systems. You will help Xenon7 validate technical decisions, shape AI/data proposals, and bring senior credibility to conversations with CTOs, Chief Data Officers, and platform engineering leaders.
This is not a full-time delivery role. The expected commitment is around 10–20 hours per month on an advisory retainer.
Responsibilities
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Join technical discovery and deep-dive conversations with enterprise technology leaders.
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Advise on enterprise AI, data platform, and orchestration architecture.
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Support XData and orchestration-layer POCs by validating architecture decisions.
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Review client proposals to ensure the proposed solutions are technically sound and realistic.
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Provide guidance on MLOps, observability, AI evaluation, and production AI governance.
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Contribute to thought leadership, such as technical content, conference talks, or market-facing insights.
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Help Xenon7 identify risks, trade-offs, and best practices when designing AI solutions for complex enterprise environments.
Requirements
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Advanced academic background in Computer Science, Machine Learning, Data Engineering, or a related field. PhD preferred; Master’s degree also considered.
•
Deep hands-on experience building enterprise data platforms in complex, multi-system environments.
•
Strong experience with production AI/ML systems, MLOps, observability, evaluation frameworks, and AI governance.
•
Experience with agentic or GenAI orchestration frameworks such as LangChain, LlamaIndex, AutoGen, Semantic Kernel, or similar.
•
Ability to advise senior technical stakeholders, including CTOs, CDOs, data leaders, and platform engineering teams.
•
Strong architectural judgment and ability to identify what is technically realistic, scalable, and enterprise-ready.
•
Strong English communication skills.
•
Bonus: experience with Microsoft AI ecosystem tools such as Azure AI, Azure OpenAI, Copilot, or Copilot Studio.
•
Bonus: experience with Snowflake, Databricks, MLflow, Kubernetes, Airflow, dbt, or similar enterprise data/AI tooling.
Benefits
•
Advisory retainer up to USD $50/hour
•
Fractional advisory engagement: approximately 10–20 hours per month
•
Remote work arrangement
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Opportunity to work directly with senior Xenon7 leadership and enterprise clients.
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Exposure to high-level AI transformation, data platform, and GenAI strategy initiatives.