EI
AI Engineer Specialist
eTeam Inc.
🇨🇦 Canada
On-site
3 weeks ago
- AI
- TypeScript
- JavaScript
- AWS
- DevSecOps
- CI/CD
- Incident Response
- Python
- Java
- C#
- REST API
- Git
- Agile
- Genesys
- Amazon Bedrock
- Bedrock
- IaC
- AWS Cloud
- DynamoDB
- IAM
- KMS
- CloudWatch
- Change Management
3 weeks ago
Location: Toronto, ON
JOB DESCRIPTION:
Primary skill - Conversational/Cognigy AI Engineer
Exp - 3yrs
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 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.
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.
- Strong proficiency in TypeScript or JavaScript; 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 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 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, 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.
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 team’s 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 · eTeam Inc.