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Shakudo

Data stack operating system for AI

Principal Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeMenlo Park, CA, USA

About the Job

Requirements

  • At least 8 years of experience across software, data, platform, infrastructure, or artificial intelligence engineering roles.
  • At least 3 years of experience building large language model or artificial intelligence applications such as retrieval-augmented generation, agents, evaluations, workflow automation, or production artificial intelligence systems.
  • At least 5 years of experience working with Kubernetes and cloud-native infrastructure in production environments.
  • Strong experience with major cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
  • Strong data engineering experience, including pipelines, orchestration, transformation, data quality, access controls, and production data workflows.
  • Experience with a modern data stack such as Apache Spark, Apache Airflow, Databricks, Snowflake, or similar technologies.
  • Experience building or deploying artificial intelligence, data, or automation solutions in highly regulated or operationally complex industries.
  • Experience applying artificial intelligence to real-world operational data such as sensor, geospatial, logistics, enterprise resource planning, field operations, or forecasting data.
  • Proficiency in at least one production programming language such as Python, Go, TypeScript, Java, or Scala.
  • Strong systems thinking across data, users, permissions, workflows, infrastructure, governance, and business processes.
  • Strong customer-facing communication skills with engineers, operators, security teams, executives, and business owners.
  • Willingness to travel to customer sites as needed.

Responsibilities

  • Embed with customer teams to understand business problems, workflows, data systems, constraints, and success metrics.
  • Define success for each engagement, including the target outcome, adoption path, production boundary, and measurable impact.
  • Translate ambiguous customer needs into technical scopes, architectures, implementation plans, and production outcomes.
  • Build and deploy artificial intelligence and data applications on Shakudo, including agentic workflows, retrieval-augmented generation systems, data pipelines, integrations, evaluations, and operational automation.
  • Design and implement production data workflows across enterprise environments, including ingestion, transformation, orchestration, data quality, access control, and observability.
  • Deploy and operate Shakudo in cloud, hybrid, on-premises, private cloud, and air-gapped customer environments.
  • Work hands-on with Kubernetes, containers, networking, storage, identity, secrets, observability, and production troubleshooting.
  • Partner with customer engineering, platform, data, and security teams to make systems live, governed, adopted, and measurable.
  • Participate in PagerDuty-based production support for customer deployments, including incident response, escalation, root-cause analysis, and remediation.
  • Turn customer-specific work into reusable patterns, playbooks, templates, and product feedback for Shakudo.

Desired Qualifications

  • Experience in a forward-deployed, professional services, solutions architecture, customer engineering, field engineering, or technical consulting role.
  • Experience delivering outcome-based customer engagements measured by adoption, operational improvement, or business impact.
  • Experience with data engineering, machine learning, or data science workflows, including feature engineering, model training, experimentation, evaluation, or production machine learning systems.
  • Experience with on-premises, private cloud, regulated, hybrid, or air-gapped deployments.
  • Experience with infrastructure as code and production operations.
  • Experience working with enterprise security, compliance, audit, access control, and governance requirements.
  • Experience integrating artificial intelligence or data systems with enterprise applications, internal application programming interfaces, data platforms, or customer-specific operational tools.
  • Experience leading senior technical stakeholders through architecture reviews, security reviews, implementation planning, and production-readiness decisions.
  • Ability to identify repeatable product and service opportunities from customer-specific implementations.

About the Company

Shakudo

Data stack operating system for AI

Shakudo provides an operating system for data and AI stacks that lets enterprise data science and ML teams build, deploy, and manage AI products. Its platform automates DevOps, unifies data tools (170+), and can be self-hosted in a client’s virtual private cloud to keep data in-house. It differentiates itself through broad compatibility, avoidance of vendor lock-in, and an end-to-end data/AI stack in one platform. The goal is to simplify and accelerate enterprise AI development and deployment with a unified, self-hosted platform.

Company size
11-50
Company stage
Series A
Total funding
$17M
Headquarters
Toronto, Canada
Founded
2021

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