Full-Time

Forward Deployed Engineer

Shakudo

Shakudo

11-50 employees

Data stack operating system for AI

No salary listed

Menlo Park, CA, USA

In Person

On-site in Menlo Park, California.

Category
Software Engineering
Required Skills
LLM
Kubernetes
Microsoft Azure
Python
Airflow
Apache Spark
Computer Networking
Java
Data Engineering
Docker
TypeScript
AWS
Go
Scala
Observability
Databricks
Snowflake
Google Cloud Platform

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Requirements
  • 8+ years of experience across software, data, platform, infrastructure, or AI engineering roles, including:
  • 3+ years building LLM/AI applications such as RAG, agents, evaluations, workflow automation, or production AI systems.
  • 5+ years working with Kubernetes and cloud-native infrastructure in production environments.
  • Strong experience with major cloud platforms such as AWS, Azure, or GCP.
  • Strong data engineering background, including pipelines, orchestration, transformation, data quality, access controls, and production data workflows.
  • Experience with a modern data stack such as Spark, Airflow, Databricks, Snowflake, or similar.
  • Experience building or deploying AI, data, or automation solutions in highly regulated or operationally complex industries, such as financial services, government, healthcare, energy, agriculture, supply chain, or industrial operations.
  • Ability to apply AI to real-world operational data, such as sensor data, geospatial data, logistics data, ERP data, field operations data, 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.
  • Excellent customer-facing communication skills with engineers, operators, security teams, executives, and business owners.
  • Strong ownership mindset: you care about production rollout, adoption, reliability, operational handoff, and measurable impact.
  • 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 what success looks like for each engagement, including the target outcome, adoption path, production boundary, and measurable impact.
  • Translate ambiguous customer needs into clear technical scopes, architectures, implementation plans, and production outcomes.
  • Build and deploy AI and data applications on Shakudo, including agentic workflows, RAG 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 complex customer environments, including cloud, hybrid, on-prem, private cloud, and air-gapped infrastructure.
  • Work hands-on with Kubernetes, containers, networking, storage, identity, secrets, observability, and production troubleshooting.
  • Partner with customer engineering, platform, data, and security teams to get systems live, governed, adopted, and measurable.
  • Participate in PagerDuty-based production support for customer deployments, including incident response, escalation, root-cause analysis, and follow-up 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 where success was 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 ML systems.
  • Experience with on-prem, 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 AI or data systems with enterprise applications, internal APIs, 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.

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 round on February 17, 2026.
  • Shakudo says major customers funded the round and joined the cap table.
  • The company targets nuclear, healthcare, finance, and logistics with sovereign AI infrastructure.

What critics are saying

  • Sales concentration risk is severe; Loblaw and CentralReach-linked investors signal customer dependence.
  • Databricks, Snowflake, and cloud hyperscalers can bundle similar governance and orchestration fast.
  • If regulated enterprises reject agent autonomy, Kaji and AI Gateway become niche features.

What makes Shakudo unique

  • Shakudo sells a self-hosted OS for enterprise AI, keeping workloads inside customer VPCs.
  • It now bundles Kaji and AI Gateway, covering agents, governance, and model control.
  • Loblaw Digital says Shakudo cut AI deployment from six months to same-day delivery.

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Benefits

Professional Development Budget

Growth & Insights and Company News

Headcount

6 month growth

8%

1 year growth

5%

2 year growth

11%
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.