AI Engineer
- Toronto, ON, Canada
- Greater Toronto Area, Canada, Canada
Full-time
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Job details
- Job type
- Full-time
- Posting language
- English
- Posted
Original job description
ARKION PlatformStandard
For Executives
Built for boards, CIOs, and audit committees
Learn
Field notes, principles, and the Standard
Tools
Estimate, scan, and act
Browse the full libraryAll resources→
PricingTeam
We’re hiring·4 roles→Free ScanScan→
PlatformStandardResourcesPricingTeamRequest Discovery Scan→We’re hiring· 4 roles →
← All open roles
LocationHybrid
Reports toChief Product Officer
Apply for this role→
This role focuses on LLM-powered agents, orchestration frameworks, and intelligent automation, not just experimentation. You will build systems that are stateful, scalable, secure, and integrated into real engineering workflows.
You will work closely with the Software Architect, Rust Backend Engineers, Senior Frontend Engineer, and Cloud & Deployment Engineer to embed AI into both: our product (NHI / security platform), and our internal engineering stack.
AI agents & orchestration
Core
Introduce AI-first workflows across engineering and deployment.
02
Improve developer velocity and product quality.
03
Reduce manual effort across teams.
04
Help build a modern, AI-driven engineering platform.
Ready to apply?
Email your application directly to FR03@arkion.ai. Include the following so we can move quickly:
ARKION
The governance layer for non-human identity. Purpose-built for the machine estate beneath the enterprise: AI agents, service accounts, and the cryptographic substrate underneath them.
Product
© 2026 Arkion Identity Systems, Inc.
For Executives
Built for boards, CIOs, and audit committees
- Executive Brief
- Compliance Crosswalk
- Cost of Inaction
- Trust Center· soon
Learn
Field notes, principles, and the Standard
- The NHIG Standard
- Field Notes
- AI Agent Governance
- Certificate Lifecycle
- Identity Registry
- Why Now
Tools
Estimate, scan, and act
- Risk Estimator
- Discovery Scan
- Implementation Timeline
Browse the full libraryAll resources→
PricingTeam
We’re hiring·4 roles→Free ScanScan→
PlatformStandardResourcesPricingTeamRequest Discovery Scan→We’re hiring· 4 roles →
← All open roles
- Engineering
- AI Platform
LocationHybrid
- Greater Toronto Area
Reports toChief Product Officer
Apply for this role→
- About the Role
This role focuses on LLM-powered agents, orchestration frameworks, and intelligent automation, not just experimentation. You will build systems that are stateful, scalable, secure, and integrated into real engineering workflows.
You will work closely with the Software Architect, Rust Backend Engineers, Senior Frontend Engineer, and Cloud & Deployment Engineer to embed AI into both: our product (NHI / security platform), and our internal engineering stack.
- Responsibilities
AI agents & orchestration
- Design and implement AI agents capable of code generation, review, and refactoring.
- Build agents for test generation and validation.
- Build agents for deployment automation and troubleshooting.
- Build agents for documentation generation and knowledge retrieval.
- Build multi-step, stateful workflows using tool calling, task planning, and execution graphs.
- Build systems using OpenAI SDK, Anthropic SDK, and AWS AgentCore.
- Design and implement memory strategies: short-term (context window), long-term (vector DB / retrieval), and session-based memory for agents.
- Use frameworks such as LangGraph, LangChain / LlamaIndex (or similar).
- Implement Retrieval-Augmented Generation (RAG), tool/function calling, and multi-agent coordination.
- Build tools that assist engineers working in Rust, Next.js, and cloud-native systems.
- Generate boilerplate code, tests, and API integrations.
- Improve debugging and observability workflows.
- Integrate AI into Git workflows (PRs, reviews, commits), CI/CD pipelines, and internal developer tools.
- Deploy AI systems in Kubernetes environments and containerized systems (Docker).
- Build AI-driven systems for deployment validation, incident analysis, and cloud cost optimization.
- Ensure reliability, scalability, and observability of AI pipelines.
- Required Skills
Core
- Strong experience designing and shipping production-grade AI systems (not just experimentation).
- Hands-on experience with LLM SDKs (OpenAI, Anthropic) and orchestration frameworks (LangGraph, LangChain, LlamaIndex, or equivalent).
- Experience implementing RAG, tool/function calling, and multi-agent coordination.
- Familiarity with vector databases and short/long-term memory strategies.
- Comfortable working across engineering, product, and infrastructure.
- Experience deploying AI services in containerized / Kubernetes environments.
- Who You Are
- You think in systems, workflows, and automation, not just models.
- You focus on real-world impact and production readiness.
- You are comfortable working across engineering, product, and infrastructure.
- You enjoy building tools that other engineers rely on daily.
- You thrive in high-ownership, fast-moving environments.
- Why Join Us
Introduce AI-first workflows across engineering and deployment.
02
Improve developer velocity and product quality.
03
Reduce manual effort across teams.
04
Help build a modern, AI-driven engineering platform.
Ready to apply?
Email your application directly to FR03@arkion.ai. Include the following so we can move quickly:
- Resume
- GitHub or portfolio (AI or automation projects)
- Examples of AI agents, workflow orchestration systems, or developer productivity tools
ARKION
The governance layer for non-human identity. Purpose-built for the machine estate beneath the enterprise: AI agents, service accounts, and the cryptographic substrate underneath them.
Product
- Platform
- Capabilities
- Discovery Scan
- Executive Brief
- Compliance
- Cost of Inaction
- Risk Estimator
- NHIG Guide
- The NHIG Standard
- Vocabulary
- Field Notes
- AI Agent Governance
- Certificate Lifecycle
- Identity Registry
- About
- Team
- Careers
- Pricing
- Contact
- Trust Center
- Security
- Privacy
- Terms
© 2026 Arkion Identity Systems, Inc.
More about this job
Responsibilities
Design and deploy production-grade AI agents and stateful workflows for code generation, testing, review, deployment, troubleshooting, and documentation. Integrate AI into developer tools, Git workflows, CI/CD, and cloud environments, ensuring systems are reliable, scalable, and observable.
Requirements
The role requires experience shipping production AI systems, using LLM SDKs and orchestration frameworks, and implementing RAG, tool calling, multi-agent coordination, and memory strategies. Candidates should also have experience deploying AI services in containers or Kubernetes and be comfortable working across engineering, product, and infrastructure.
Skills
- Production-Grade AI Systems
- LLM SDKs
- AI Agent Orchestration
- LangGraph
- LangChain
- LlamaIndex
- Retrieval-Augmented Generation
- Tool and Function Calling
- Multi-Agent Coordination
- Vector Databases
- Memory Management
- Rust
- Next.js
- Kubernetes
- Docker
- CI/CD
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
- Data & Analytics
- Security & Safety
Keywords
- Artificial Intelligence
- Large Language Models
- OpenAI SDK
- Anthropic SDK
- AWS AgentCore
- LangGraph
- LangChain
- LlamaIndex
- Retrieval-Augmented Generation
- Tool Calling
- Function Calling
- Multi-Agent Coordination
- Vector Databases
- Agent Memory
- Code Generation
- Test Generation
- Rust
- Next.js
- Kubernetes
- Docker
- Git Workflows
- CI/CD
- Deployment Automation
- Observability
- Cloud Cost Optimization
- Developer Productivity
- Security Platform
- Stateful Workflows