Job Overview:

Requirement/Must Have:

- 4+ years of professional software engineering, application development, or systems analysis experience.
- Demonstrated experience delivering production software across the full software development lifecycle.
- Strong proficiency in TypeScript or JavaScript.
- Experience designing and consuming RESTful APIs and integrating distributed systems.
- Experience with cloud platforms, preferably AWS, including services, configuration, deployment, monitoring, or infrastructure automation.
- Experience with CI/CD pipelines, Git-based source control, automated testing, and DevSecOps practices.
- Ability to diagnose complex technical problems and deliver reliable, maintainable solutions.
- Experience working in an agile product or delivery team with multiple internal partners.
- Strong verbal and written communication skills, including the ability to explain technical topics to both technical and non-technical stakeholders.
- Ability to work independently, manage competing priorities, and deliver commitments in a changing workplace.

Responsibilities:

- Design, develop, test, debug, document, and deploy secure software solutions for Digital Assistants and related conversational AI capabilities.
- Build and maintain integrations between chatbot experiences, SaaS platforms, enterprise APIs, customer-data services, contact-center capabilities, and other internal systems.
- Configure and extend conversational AI capabilities, including Cognigy-based flows, services, APIs, and supporting automation.
- Develop and maintain TypeScript/JavaScript services, API integrations, event-driven components, and cloud-based solutions.




- Contribute to AWS infrastructure, deployment pipelines, environment configuration, monitoring, and operational support.
- Apply DevSecOps practices throughout the delivery lifecycle, including source control, automated testing, code quality checks, CI/CD, vulnerability remediation, and release controls.
- Troubleshoot production and non-production issues using logs, monitoring, traces, test results, and other diagnostic tools.
- Identify root causes and implement durable fixes.
- Develop automated tests and regression coverage for bot behavior, APIs, integrations, and supporting services.
- Participate in solution design, story refinement, estimation, sprint planning, demonstrations, retrospectives, and peer reviews.
- Collaborate with engineers, contractors, product owners, UX professionals, architects, security partners, and business stakeholders to deliver high-quality outcomes.
- Create and maintain technical documentation, runbooks, operational procedures, and knowledge-transfer materials.
- Identify opportunities to improve reliability, observability, automation, maintainability, performance, and developer productivity.
- Provide constructive technical guidance and peer support to other team members while operating within established team architecture and engineering direction.




- Support production releases, incident response, defect remediation, and after-hours support activities when required by the team.

Nice to Have:

- Experience with Cognigy or another enterprise conversational AI, chatbot, virtual-assistant, or customer-service automation platform.
- Experience integrating chatbots with contact-center platforms, live-chat capabilities, Client, session management, authentication, or customer-data services.
- Experience with Amazon Bedrock and LLM integration: Bedrock, Agentcore.
- Experience with AWS serverless, API management, infrastructure as code, observability, or application performance monitoring.
- Experience with AWS cloud development: Lambda, S3, DynamoDB, IAM, KMS, and CloudWatch.
- Experience building automated regression suites and test tooling for conversational experiences and integrations.
- Experience with enterprise security controls, PII-aware design, vulnerability remediation, and secure API development.
- Insurance, financial services, retirement solutions, or other regulated-industry experience.
- Experience mentoring peers, leading feature-level technical execution, or coordinating delivery across multiple teams.

Skills:

- Conversational AI.
- Cognigy AI.
- TypeScript.
- JavaScript.
- Python.
- Java.
- C#.
- RESTful APIs.
- AWS.
- CI/CD.
- Git.
- DevSecOps.
- Amazon Bedrock.
- LLM.
- Lambda.
- S3.
- DynamoDB.
- IAM.
- KMS.
- CloudWatch.

Qualification And Education:

- Four or more years of professional software engineering, application development, or systems analysis experience.

📌 AI Engineer Specialist (Toronto)
🏢 Cynet Systems
📍 Toronto