Senior Tech Lead - Engineering

hireVouch; Canada; Remote; CAD 140.000 - 200.000; Vollzeit

Zusammenfassung

hireVouch seeks a Senior Technical Lead to drive end‑to‑end cloud engineering, DevOps and AI‑powered development across AWS and Kubernetes platforms. This hands‑on leadership role emphasizes architecture, security, automation and scalable delivery pipelines.

You will mentor teams, define standards, and partner with stakeholders to elevate platform reliability and performance while enabling rapid, secure software releases.

Qualifikationen

• Significant experience in a Senior DevOps, Cloud Engineering, Platform Engineering or Technical Lead role.
• Strong hands‑on experience with AWS, including EC2, EKS, S3, IAM, VPC, RDS, CloudWatch and Lambda.
• Extensive experience with Kubernetes (K8s) and containerisation such as Docker.
• Proficiency with Infrastructure as Code tools such as Terraform, CloudFormation or Pulumi.
• Strong experience building and managing CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI or Azure DevOps.
• Experience with configuration management and automation tools such as Ansible.
• Strong scripting and automation skills using Python, Bash or Go.
• Experience with monitoring and observability tools such as Prometheus, Grafana, Datadog or ELK.
• Strong understanding of networking, security, distributed systems and cloud architecture.
• Experience with microservices and modern software development architectures.

Aufgaben

• Provide technical leadership and direction across engineering and DevOps teams.
• Define and implement scalable, resilient and secure cloud-native architectures.
• Lead technical design discussions, architecture reviews and technology decisions.
• Establish engineering standards, best practices and development guidelines.
• Drive continuous improvement across infrastructure, application delivery and operational processes.
• Mentor engineers and support the development of technical capabilities within the team.
• Design, build and manage cloud infrastructure primarily within AWS.
• Develop and maintain highly available, scalable and secure cloud environments.
• Manage containerised applications and orchestration platforms using Kubernetes (K8s).
• Implement and maintain infrastructure automation and Infrastructure as Code (IaC).
• Optimise cloud infrastructure for performance, availability, security and cost efficiency.
• Manage networking, IAM, storage, compute and cloud security configurations.
• Design, implement and optimise CI/CD pipelines and automated deployment processes.
• Drive automation across build, test, release and deployment workflows.
• Champion DevOps culture, collaboration and continuous delivery practices.
• Implement monitoring, logging, alerting and observability solutions.
• Improve system reliability through automation, incident management and proactive problem-solving.
• Establish and promote effective release management and deployment strategies.
• Drive platform stability, scalability, resilience and operational excellence.
• Implement best practices around disaster recovery, backup and business continuity.
• Embed security best practices throughout the development and deployment lifecycle.
• Identify and resolve complex infrastructure and production performance issues.
• Promote Site Reliability Engineering (SRE) principles and practices.
• Explore, design and implement AI-driven solutions to enhance engineering productivity, automation and operational efficiency.
• Work with Generative AI technologies, Large Language Models (LLMs) and AI-powered development tools.
• Design and support the integration of AI agents and agentic workflows into existing applications, platforms and business processes.
• Understand agentic AI architectures, including autonomous agents, tool calling, orchestration, multi-agent systems and workflow automation.
• Leverage AI coding assistants and development tools to improve software engineering productivity, code quality and delivery speed.
• Support the deployment, integration and scaling of AI/ML workloads within AWS and Kubernetes environments.
• Work with AI APIs and frameworks such as OpenAI, Amazon Bedrock, LangChain or LangGraph.
• Understand the infrastructure, security, scalability and governance considerations associated with deploying and operating AI-powered applications.
• Champion the responsible adoption of AI technologies across engineering teams, identifying opportunities to automate repetitive tasks and improve technical delivery.

Kenntnisse

AWS

Kubernetes

Cloud architecture

CI/CD

IaC

Security

Monitoring

Leadership

Tools

Terraform

Ansible

GitHub Actions

Docker

Jobbeschreibung

The Opportunity

We are seeking an experienced Senior Technical Lead with a strong background in DevOps, Cloud Engineering , AI Engineering and modern infrastructure technologies to lead the design, development and evolution of our technology platforms. This is a hands‑on technical leadership role for someone who combines deep expertise in AWS, Kubernetes and cloud-native technologies with the ability to drive engineering best practices, lead technical initiatives and mentor development and infrastructure teams. The successful candidate will play a key role in shaping our cloud architecture, improving platform scalability, reliability and security, and driving automation across our software delivery lifecycle.

Key Responsibilities

Technical Leadership & Architecture

• Provide technical leadership and direction across engineering and DevOps teams.
• Define and implement scalable, resilient and secure cloud-native architectures.
• Lead technical design discussions, architecture reviews and technology decisions.
• Establish engineering standards, best practices and development guidelines.
• Drive continuous improvement across infrastructure, application delivery and operational processes.
• Mentor engineers and support the development of technical capabilities within the team.

Cloud & Infrastructure Engineering

• Design, build and manage cloud infrastructure primarily within AWS.
• Develop and maintain highly available, scalable and secure cloud environments.
• Manage containerised applications and orchestration platforms using Kubernetes (K8s).
• Implement and maintain infrastructure automation and Infrastructure as Code (IaC).
• Optimise cloud infrastructure for performance, availability, security and cost efficiency.
• Manage networking, IAM, storage, compute and cloud security configurations.

DevOps & CI/CD

• Design, implement and optimise CI/CD pipelines and automated deployment processes.
• Drive automation across build, test, release and deployment workflows.
• Champion DevOps culture, collaboration and continuous delivery practices.
• Implement monitoring, logging, alerting and observability solutions.
• Improve system reliability through automation, incident management and proactive problem-solving.
• Establish and promote effective release management and deployment strategies.

Platform Reliability & Security

• Drive platform stability, scalability, resilience and operational excellence.
• Implement best practices around disaster recovery, backup and business continuity.
• Embed security best practices throughout the development and deployment lifecycle.
• Identify and resolve complex infrastructure and production performance issues.
• Promote Site Reliability Engineering (SRE) principles and practices.

AI, Generative AI & Agentic Engineering

Explore, design and implement AI-driven solutions to enhance engineering productivity, automation and operational efficiency. Work with Generative AI technologies, Large Language Models (LLMs) and AI-powered development tools. Design and support the integration of AI agents and agentic workflows into existing applications, platforms and business processes. Understand agentic AI architectures, including autonomous agents, tool calling, orchestration, multi-agent systems and workflow automation. Leverage AI coding assistants and development tools to improve software engineering productivity, code quality and delivery speed. Support the deployment, integration and scaling of AI/ML workloads within AWS and Kubernetes environments. Work with AI APIs and frameworks such as OpenAI, Amazon Bedrock, LangChain or LangGraph. Understand the infrastructure, security, scalability and governance considerations associated with deploying and operating AI-powered applications. Champion the responsible adoption of AI technologies across engineering teams, identifying opportunities to automate repetitive tasks and improve technical delivery.

Additional AI & Agentic Technology Experience

• Generative AI, LLMs and prompt engineering.
• Agentic AI frameworks and architectures.
• AI agent orchestration and multi-agent workflows.
• Amazon Bedrock or equivalent enterprise AI platforms.
• LangChain, LangGraph, CrewAI or similar frameworks.
• Integration of AI models and services through APIs.
• Deploying and managing AI-powered applications in cloud-native environments.
• AI-assisted software development tools such as GitHub Copilot, Cursor or Claude Code.
• Understanding of RAG (Retrieval-Augmented Generation), vector databases and AI application architecture.

AI & Agentic Mindset

We are looking for someone who is genuinely interested in the evolution of AI and agentic technologies, and who can help the organisation understand how these capabilities can be practically applied across its technology landscape. The successful candidate should be comfortable experimenting with emerging AI tools, identifying opportunities for intelligent automation and helping engineering teams adopt AI-enabled development practices.

Required Skills & Experience

• Significant experience in a Senior DevOps, Cloud Engineering, Platform Engineering or Technical Lead role.
• Strong hands‑on experience with AWS, including services such as EC2, EKS, S3, IAM, VPC, RDS, CloudWatch and Lambda.
• Extensive experience with Kubernetes (K8s) and containerisation technologies such as Docker.
• Strong experience designing and managing cloud-native infrastructure.
• Proficiency with Infrastructure as Code tools such as Terraform, CloudFormation or Pulumi.
• Strong experience building and managing CI/CD pipelines using tools such as Jenkins, GitHub Actions, GitLab CI or Azure DevOps.
• Experience with configuration management and automation tools such as Ansible.
• Strong scripting and automation skills using Python, Bash or Go.
• Experience with monitoring and observability tools such as Prometheus, Grafana, Datadog or ELK.
• Strong understanding of networking, security, distributed systems and cloud architecture.
• Experience working with microservices and modern software development architectures.
• Excellent troubleshooting and problem‑solving capabilities.

Leadership & Communication

• Proven ability to lead technical teams and influence engineering direction.
• Strong communication skills with the ability to engage both technical and non-technical stakeholders.
• Experience mentoring engineers and promoting a culture of knowledge sharing.
• Ability to balance hands‑on technical delivery with strategic technical decision‑making.
• Comfortable taking ownership of complex technical challenges and driving initiatives through to completion.
• A proactive mindset with a passion for engineering excellence and continuous improvement.

Nice to Have

• AWS certifications (Solutions Architect Professional, DevOps Engineer Professional or equivalent).
• Experience with AWS EKS and large‑scale Kubernetes environments.
• Exposure to service mesh technologies such as Istio or Linkerd.
• Experience with GitOps tools such as ArgoCD or Flux.
• Experience with Helm and Kubernetes operators.
• Knowledge of serverless architectures and event‑driven systems.
• Experience implementing SRE practices, SLIs, SLOs and error budgets.
• Experience in highly regulated or enterprise‑scale environments.

What We're Looking For

We are looking for a technically strong leader who can operate at both architectural and implementation levels. Someone who enjoys solving complex engineering problems, building scalable cloud platforms, driving DevOps transformation and helping engineering teams deliver high‑quality software faster and more reliably. The ideal candidate will be a hands‑on technical leader rather than purely a people manager, with the credibility and experience to influence architecture, guide engineering teams and take ownership of mission‑critical platforms.