Senior Full Stack Gen AI Engineer/Technical Engagement Manager
Role Overview
Join Straive as a Senior Full Stack AI Engineer combining hands-on engineering with technical engagement and project delivery leadership.
Work directly with business and client stakeholders to shape requirements, define solutions, coordinate delivery, and support productionization.
Operate across backend, frontend, databases, APIs, cloud, DevOps, enterprise integrations, and Generative AI.
Key Skills for This Role
Full Job Posting
Role overview
Join Straive as a Senior Full Stack AI Engineer combining hands-on engineering with technical engagement and project delivery leadership.
Work directly with business and client stakeholders to shape requirements, define solutions, coordinate delivery, and support productionization.
Operate across backend, frontend, databases, APIs, cloud, DevOps, enterprise integrations, and Generative AI.
Location and employment
- The role is based in Calgary, Canada, with a hybrid work arrangement.
- The employment type is full-time.
Full-stack engineering
- Design, build, test, deploy, and support production-grade full-stack applications.
- Develop scalable backend services, REST APIs, integrations, and reusable frontend components.
- Remain hands-on with coding, debugging, code reviews, architecture decisions, and technical problem solving.
- Build for performance, maintainability, security, reliability, and user experience.
Technical engagement and delivery
- Act as technical engagement lead for client and internal projects and translate business needs into solution designs and delivery plans.
- Own technical planning, estimation, sprint or milestone execution, delivery tracking, and coordination across engineering, data, QA, product, and business teams.
- Identify and resolve risks, dependencies, integration constraints, and production-readiness issues.
- Lead discovery workshops, solution walkthroughs, demos, and client discussions.
Cloud, DevOps, and productionization
- Move solutions from prototype or development environments into stable, production-grade applications.
- Design and implement CI/CD, build, release, deployment, and rollback processes.
- Deploy, operate, monitor, and scale applications using cloud platforms and containerized environments.
- Implement logging, observability, exception handling, testing, security controls, and performance monitoring.
- Partner with platform, infrastructure, security, and client IT teams on operational readiness.
Data and Generative AI
- Design relational or NoSQL data models, application data flows, persistence layers, and integration patterns.
- Develop integrations using APIs, messaging, event-driven approaches, or batch interfaces.
- Build or integrate LLM capabilities, agentic workflows, RAG solutions, embeddings, and vector databases where relevant.
Team leadership
- Coach and mentor junior and mid-level engineers through design discussions, pair problem solving, code reviews, and development guidance.
- Reinforce engineering standards for architecture, coding, testing, documentation, version control, security, and release management.
- Break complex problems into manageable work packages and contribute to continuous improvement.
Required qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
- 5–10 years of experience in full-stack development, software engineering, application engineering, or a closely related role.
- Experience building and deploying production-grade web applications and backend services.
- Experience owning technical workstreams or projects and coordinating delivery across contributors or functions.
- Experience mentoring developers, reviewing technical work, and guiding engineering delivery.
- Experience working with business or client stakeholders to translate requirements into technical solutions.
- Strong programming skills in Python and/or JavaScript/TypeScript.
- Experience with backend frameworks, React.js, SQL databases, REST APIs, authentication, Git, testing, CI/CD, Docker, and cloud platforms.
- Understanding of architecture, secure development, debugging, code quality, performance, deployment, observability, monitoring, and production support.
Preferred qualifications
- Experience in oil and gas, energy, utilities, energy retail, or marketing analytics environments.
- Experience with microservices, Kubernetes, distributed systems, messaging, event-driven architectures, or data-intensive applications.
- Exposure to AI/ML or Generative AI application development and enterprise LLM integration.
- Familiarity with Azure OpenAI/OpenAI, LangChain, vector databases, or RAG architectures.
- Consulting, client-facing delivery, technical project management, or engagement management experience.
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