Role Name: AI Engineer Specialist Location: Toronto, ON JOB DESCRIPTION: Primary skill - Conversational/Cognigy AI Engineer Exp - yrs Key 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 Type

Script/Java

Script services, API integrations, event-driven components, and cloud-based solutions.

Contribute to AWS infrastructure, deployment pipelines, environment configuration, monitoring, and operational support.

Apply Dev

SecOps 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.

Required Skills and Experience: Four or more years of professional software engineering, application development, or systems analysis experience.

Demonstrated experience delivering production software across the full software development lifecycle.

Robust proficiency in Type

Script or Java

Script; experience with another modern programming language such as Python, Java, or C is beneficial.

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 Dev

SecOps 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 written and verbal 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 environment.

Preferred Skills and Experience: 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, Genesys, 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, S, DynamoDB, IAM, KMS, and Cloud

Watch.

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.

Working Model and Collaboration Expectations: Work as an embedded member of the Digital Assistants engineering pod.

Partner with an Engineering Lead who provides technical direction, architecture alignment, prioritization support, and final engineering accountability.

Coordinate closely with product, UX, architecture, security, QA, operations, and business stakeholders.

Participate in team ceremonies and maintain regular communication through the teams approved collaboration and development tools.

Follow access, security, data-handling, SDLC, change-management, and production-support procedures.

Provide documentation and knowledge transfer sufficient to support continuity across the team.

Expected Outcomes: Deliver committed features, enhancements, integrations, and defect fixes with a high level of quality.

Improve the reliability, security, observability, and maintainability of Digital Assistants capabilities.

Increase automated test coverage and reduce avoidable manual deployment or operational effort.

Resolve production issues efficiently and contribute to sustainable root-cause remediation.

Maintain clear technical documentation and effective collaboration with the broader Digital Assistants organization.

📌 AI Engineer Specialist (Toronto)
🏢 eTeam
📍 Toronto