S

Shakudo

Data stack operating system for AI

Principal Engineer

Full-Time
No salary listed
Senior, Expert
Menlo Park, CA, USA
In PersonTravel to customer sites is required as needed.
Software EngineeringAI Application Engineering

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 provides an operating system for data and artificial intelligence stacks that helps teams build, deploy, and manage AI products. The platform works by automating DevOps tasks and integrating over 170 different open-source and commercial tools into a single environment that can be self-hosted for better data security. It distinguishes itself from competitors by creating compatibility between many different software tools, which prevents companies from being locked into a single vendor's ecosystem. The company's goal is to reduce engineering overhead and complexity so that data science teams can focus on developing AI solutions more quickly.

Company Size

11-50

Company Stage

Series A

Total Funding

$17M

Headquarters

Toronto, Canada

Founded

2021

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Simplify Jobs

Simplify's Take

What believers are saying

  • Wittington Ventures led Shakudo's $7 million February 17, 2026 strategic round.
  • Loblaw said Shakudo cut AI deployment from six months to same-day delivery.
  • Whitecap's June 2026 case study shows Shakudo expanding from analytics into advanced AI.

What critics are saying

  • Shakudo depends on regulated-enterprise wins; losing Loblaw damages credibility by 2027.
  • AWS, Databricks, and Snowflake compress Shakudo's differentiation through bundled platforms.
  • One serious governance failure turns Shakudo into an existential compliance liability.

What makes Shakudo unique

  • Shakudo runs inside customer VPCs, keeping models and data under enterprise control.
  • Its February 17, 2026 launch bundled Kaji, AI Gateway, and Compass governance.
  • Loblaw and Whitecap adopted Shakudo in 2026 for standardized in-house AI operations.

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Benefits

Professional Development Budget

Growth & Insights and Company News

Headcount

6 month growth

12%

1 year growth

5%

2 year growth

0%
BetaKit
Feb 17th, 2026
Toronto's Shakudo converts customers into investors with $7M Series A2 raise

Toronto-based Shakudo has raised $7 million USD in a Series A2 round led by Wittington Ventures, the venture arm of the Weston family's holding company that controls Loblaw and Shoppers Drug Mart. The round attracted investment from existing customers, including CentralReach executives who personally backed the company. Founded in 2021, Shakudo provides AI infrastructure software that helps enterprises deploy AI tools securely within their existing systems. Loblaw reportedly reduced its AI development cycles from six months to same-day delivery using Shakudo's platform. The round included participation from Golden Ventures, GreatPoint Ventures, and RTP Global, bringing total funding to approximately $18 million USD. The company has grown sevenfold since its $7.2-million USD Series A in early 2023 and plans to raise a larger Series B within two years.

Shakudo
Feb 17th, 2026
Shakudo raises $7M to power sovereign enterprise AI with new autonomous agents

Shakudo, a platform providing operating systems for enterprise AI, has raised $7 million in a strategic funding round led by Wittington Ventures, a venture capital firm affiliated with Loblaw Companies Limited. The round included participation from existing investors Golden Ventures, GreatPoint Ventures and RTP Global, as well as personal investments from enterprise customers. The San Francisco and Toronto-based company will use the funding to expand its US operations and launch two new products: Kaji, an autonomous AI agent running within customers' Virtual Private Clouds, and Shakudo AI Gateway, a control plane for managing models and agents across organisations. Shakudo's platform deploys natively within customers' infrastructure, ensuring intellectual property remains within the organisation whilst targeting regulated industries including nuclear energy, healthcare and financial services.

BetaKit
Jul 5th, 2023
Shakudo closes $9.5M Series A to help companies adopt generative AI

Toronto-based Shakudo has secured $9.5 million CAD in Series A funding to help companies launch artificial intelligence products more quickly and cost-effectively.

BetaKit
Nov 3rd, 2021
Rebranded Shakudo raises $4.2 million to expand reach of AI platform

Toronto-based software startup Shakudo has rebranded from DevSentient, raising $4.2 million CAD in seed funding to expand the reach of its AI platform for data science and ML teams.