AI-Directed Software Engineer

<h3>Accountabilities</h3><li>Own the end-to-end delivery of software features, from requirements and technical specifications to demonstrations, production releases, and ongoing maintenance.</li><li>Direct AI coding tools to generate and refine code across backend services, frontend applications, database queries, APIs, infrastructure configurations, and development workflows.</li><li>Break down complex product requirements into structured, specification-driven tasks that AI systems can execute efficiently and consistently.</li><li>Review, test, debug, and harden AI-generated code to ensure correctness, reliability, security, performance, and production readiness.</li><li>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.</li><li>Design and optimize database schemas, SQL queries, and data flows, primarily using PostgreSQL.</li><li>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.</li><li>Build and maintain containerized applications using Docker and Kubernetes, including deployment configurations managed through Helm or Kustomize.</li><li>Design and implement AI-powered agents using Amazon Bedrock, including model integrations, action groups, tool calling, and Knowledge Bases for retrieval-augmented generation (RAG).</li><li>Implement appropriate safeguards for AI agents, including guardrails, evaluation frameworks, failure handling, and human-in-the-loop checkpoints for consequential decisions.</li><li>Monitor application reliability, cloud resource utilization, AI token consumption, and infrastructure costs to ensure efficient and sustainable operations.</li><li>Apply security best practices, including least-privilege access controls, secure integrations, and careful validation of AI-generated infrastructure and application code.</li><li>Improve observability and troubleshooting through logging, monitoring, testing, and operational tooling.</li><li>Establish and document reusable AI-directed development workflows, prompts, evaluation methods, and engineering standards.</li><li>Continuously improve development throughput, cycle time, and delivery consistency across assigned workstreams.</li><li>Collaborate with colleagues to challenge assumptions, resolve technical problems, and promote effective adoption of AI-directed software development practices.</li><h2>Requirements</h2><li>Strong software engineering fundamentals, including API design, distributed systems, debugging, data flows, and system architecture.</li><li>At least three years of hands-on AWS experience building, deploying, and operating production workloads.</li><li>Practical knowledge of AWS security and infrastructure, including IAM permissions, VPC networking, service reliability, cloud resource management, and cost optimization.</li><li>Experience with infrastructure as code on AWS, preferably using CloudFormation. Familiarity with AWS CDK or Terraform is also acceptable.</li><li>Broad full-stack engineering capabilities, with the ability to move between backend services, frontend development, database work, and deployment configuration.</li><li>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.</li><li>Demonstrated experience using AI-powered coding tools, such as Claude Code, Cursor, GitHub Copilot, or equivalent platforms, to deliver real software projects.</li><li>Strong code review and debugging skills, particularly when identifying subtle errors, security vulnerabilities, edge cases, and deployment issues in AI-generated output.</li><li>Experience designing and maintaining reliable software systems, with an understanding of how individual components interact under real-world workloads.</li><li>Excellent written communication skills and the ability to formulate clear, precise prompts, technical specifications, and implementation instructions.</li><li>A proactive, adaptable mindset and the ability to work effectively in a fast-paced environment where requirements, tools, and development practices evolve rapidly.</li><li>A delivery-oriented approach, balancing sound engineering judgment with the ability to ship functional software quickly.</li><li>Willingness to question assumptions, critically evaluate AI-generated recommendations, and take full responsibility for the quality of delivered solutions.</li><li>Strongly preferred: hands-on experience with Amazon Bedrock, including model invocation, agent development, action groups, tool integrations, Knowledge Bases, RAG, and Guardrails.</li><li>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.</li><li>Strongly preferred: familiarity with agent orchestration patterns, Model Context Protocol (MCP), multi-step tool execution, and human-in-the-loop workflows.</li><li>Nice to have: experience with Java, Jersey, Angular, React, PostgreSQL, or related technologies.</li><li>Nice to have: experience working with library systems, public-sector technology, or multi-tenant software-as-a-service (SaaS) platforms.</li><li>Ability to demonstrate measurable improvements in development speed, delivery consistency, and software quality through effective AI-directed engineering practices.</li><h2>Benefits</h2><li>
<strong>Employment type:</strong>Full-time, regular employment.</li><li>
<strong>Remote work:</strong>Remote working opportunity based in Canada.</li><li>
<strong>AI-first engineering environment:</strong>The opportunity to use advanced AI coding tools as a core part of the software development lifecycle.</li><li>
<strong>Broad technical exposure:</strong>Work across backend and frontend development, AWS infrastructure, DevOps, databases, and AI-powered applications.</li><li>
<strong>Applied AI innovation:</strong>Build and deploy Amazon Bedrock-based agents and intelligent workflows that address practical product and operational needs.</li><li>
<strong>Technical ownership:</strong>Manage features throughout the development lifecycle, from initial design to production deployment and operational support.</li><li>
<strong>Professional growth:</strong>Develop expertise in AI-directed software engineering, cloud architecture, agent orchestration, and modern development practices.</li><li>
<strong>Process innovation:</strong>Help establish scalable workflows and engineering standards that improve software delivery speed and consistency.</li><li>
<strong>Meaningful product contribution:</strong>Build technology that supports self-service, operational efficiency, and improved access to library services.</li><li>
<strong>Collaborative environment:</strong>Work with a team focused on innovation, continuous improvement, technical quality, and practical problem-solving.</li><li>
<strong>Inclusive workplace:</strong>An equal opportunity employment environment committed to fair hiring and professional opportunities.</li>