This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for an AI-Directed Software Engineer based in Canada.
As an AI-Directed Software Engineer, you will build and deliver production-ready software by leveraging artificial intelligence to accelerate development across the full technology stack. You will take ownership of features from initial concept through implementation, testing, deployment, and production operations, working across backend services, frontend applications, databases, and cloud infrastructure. Using AI coding tools as your primary implementation engine, you will transform product requirements into clearly defined tasks and guide AI-generated solutions toward reliable, secure, and scalable outcomes. You will also develop intelligent agent workflows using Amazon Bedrock, integrating advanced AI capabilities directly into software products. This role combines full-stack engineering, cloud architecture, DevOps, and applied AI in a fast-moving, innovation-driven environment. You will help establish repeatable AI-directed development practices, improve delivery speed, and shape the future of software engineering.
- Own the end-to-end delivery of software features, from requirements and technical specifications to demonstrations, production releases, and ongoing maintenance.
- Direct AI coding tools to generate and refine code across backend services, frontend applications, database queries, APIs, infrastructure configurations, and development workflows.
- Break down complex product requirements into structured, specification-driven tasks that AI systems can execute efficiently and consistently.
- Review, test, debug, and harden AI-generated code to ensure correctness, reliability, security, performance, and production readiness.
- Develop and maintain backend services using technologies such as Java, REST APIs, and related frameworks, while contributing to frontend applications built with Angular, React, and TypeScript.
- Design and optimize database schemas, SQL queries, and data flows, primarily using PostgreSQL.
- Configure, deploy, and operate applications and services on AWS, using infrastructure-as-code practices and cloud services such as CloudFormation, IAM, VPC, S3, EFS, and CloudWatch.
- Build and maintain containerized applications using Docker and Kubernetes, including deployment configurations managed through Helm or Kustomize.
- Design and implement AI-powered agents using Amazon Bedrock, including model integrations, action groups, tool calling, and Knowledge Bases for retrieval-augmented generation (RAG).
- Implement appropriate safeguards for AI agents, including guardrails, evaluation frameworks, failure handling, and human-in-the-loop checkpoints for consequential decisions.
- Monitor application reliability, cloud resource utilization, AI token consumption, and infrastructure costs to ensure efficient and sustainable operations.
- Apply security best practices, including least-privilege access controls, secure integrations, and careful validation of AI-generated infrastructure and application code.
- Improve observability and troubleshooting through logging, monitoring, testing, and operational tooling.
- Establish and document reusable AI-directed development workflows, prompts, evaluation methods, and engineering standards.
- Continuously improve development throughput, cycle time, and delivery consistency across assigned workstreams.
- Collaborate with colleagues to challenge assumptions, resolve technical problems, and promote effective adoption of AI-directed software development practices.
Requirements
- Strong software engineering fundamentals, including API design, distributed systems, debugging, data flows, and system architecture.
- At least three years of hands-on AWS experience building, deploying, and operating production workloads.
- Practical knowledge of AWS security and infrastructure, including IAM permissions, VPC networking, service reliability, cloud resource management, and cost optimization.
- Experience with infrastructure as code on AWS, preferably using CloudFormation. Familiarity with AWS CDK or Terraform is also acceptable.
- Broad full-stack engineering capabilities, with the ability to move between backend services, frontend development, database work, and deployment configuration.
- Working knowledge of containers and Kubernetes, including the ability to troubleshoot failing pods, interpret deployment manifests, and modify Helm configurations. Candidates should be comfortable developing these skills quickly if needed.
- Demonstrated experience using AI-powered coding tools, such as Claude Code, Cursor, GitHub Copilot, or equivalent platforms, to deliver real software projects.
- Strong code review and debugging skills, particularly when identifying subtle errors, security vulnerabilities, edge cases, and deployment issues in AI-generated output.
- Experience designing and maintaining reliable software systems, with an understanding of how individual components interact under real-world workloads.
- Excellent written communication skills and the ability to formulate clear, precise prompts, technical specifications, and implementation instructions.
- A proactive, adaptable mindset and the ability to work effectively in a fast-paced environment where requirements, tools, and development practices evolve rapidly.
- A delivery-oriented approach, balancing sound engineering judgment with the ability to ship functional software quickly.
- Willingness to question assumptions, critically evaluate AI-generated recommendations, and take full responsibility for the quality of delivered solutions.
- Strongly preferred: hands-on experience with Amazon Bedrock, including model invocation, agent development, action groups, tool integrations, Knowledge Bases, RAG, and Guardrails.
- Strongly preferred: experience evaluating and validating large language model (LLM) and agent behavior in production, including evaluation datasets, automated test harnesses, and failure-handling strategies.
- Strongly preferred: familiarity with agent orchestration patterns, Model Context Protocol (MCP), multi-step tool execution, and human-in-the-loop workflows.
- Nice to have: experience with Java, Jersey, Angular, React, PostgreSQL, or related technologies.
- Nice to have: experience working with library systems, public-sector technology, or multi-tenant software-as-a-service (SaaS) platforms.
- Ability to demonstrate measurable improvements in development speed, delivery consistency, and software quality through effective AI-directed engineering practices.
Benefits
- Employment type: Full-time, regular employment.
- Remote work: Remote working opportunity based in Canada.
- AI-first engineering environment: The opportunity to use advanced AI coding tools as a core part of the software development lifecycle.
- Broad technical exposure: Work across backend and frontend development, AWS infrastructure, DevOps, databases, and AI-powered applications.
- Applied AI innovation: Build and deploy Amazon Bedrock-based agents and intelligent workflows that address practical product and operational needs.
- Technical ownership: Manage features throughout the development lifecycle, from initial design to production deployment and operational support.
- Professional growth: Develop expertise in AI-directed software engineering, cloud architecture, agent orchestration, and modern development practices.
- Process innovation: Help establish scalable workflows and engineering standards that improve software delivery speed and consistency.
- Meaningful product contribution: Build technology that supports self-service, operational efficiency, and improved access to library services.
- Collaborative environment: Work with a team focused on innovation, continuous improvement, technical quality, and practical problem-solving.
- Inclusive workplace: An equal opportunity employment environment committed to fair hiring and professional opportunities.
