Title - Senior Full Stack AI Engineer / Technical Engagement Manager
Location: Calgary ,Canada (Hybrid-3 days in a week)
Role- Full Time with SG analytics(Staive)
Experience level- 5 to 10 years
Mandatory-hands-on with coding
Skill required - backend services, REST APIs, integrations, integrate agentic workflows, RAG, Generative AI,
Role Overview
We are seeking a Senior Full Stack AI Engineer who can combine strong hands-on software engineering with technical engagement and project delivery leadership. The successful candidate will remain close to the code while also working directly with business and client stakeholders to shape requirements, define solution approaches, coordinate delivery, and ensure successful productionization.
The ideal candidate will have 5-10 years of experience building and deploying modern enterprise applications across backend, frontend, databases, APIs, cloud, and DevOps. In addition to individual technical contribution, this person should be comfortable coaching junior engineers, reviewing technical work, managing delivery risks and dependencies, and acting as the technical point of contact for an engagement.
This role is particularly suited to someone who enjoys operating at the intersection of engineering and delivery: translating business problems into practical technical solutions, driving execution from discovery through production, and ensuring solutions are scalable, reliable, maintainable, and usable by end customers.
Key Responsibilities
Full Stack Application Engineering
· Design, build, test, deploy, and support production-grade full-stack applications from solution design through implementation and ongoing enhancement.
· Develop scalable backend services, REST APIs, integrations, and reusable frontend components for enterprise applications and internal platforms.
· Remain hands-on with coding, debugging, code reviews, architecture decisions, and technical problem solving across the delivery lifecycle.
· Build solutions with strong attention to performance, maintainability, security, reliability, and user experience.
Technical Engagement & Project Delivery
· Act as the technical engagement lead for projects, working with client and internal stakeholders to understand business needs, clarify requirements, and translate them into solution designs and delivery plans.
· Own technical work planning, effort estimation, sprint or milestone execution, delivery tracking, and coordination across engineering, data, QA, product, and business teams.
· Identify technical risks, dependencies, integration constraints, and production-readiness issues early, and drive them to resolution.
· Communicate project status, technical decisions, trade-offs, risks, and recommendations clearly to both technical and non-technical stakeholders.
· Support discovery workshops, solution walkthroughs, demos, and client discussions as the senior technical representative for the engagement.
Productionization, Cloud & DevOps
· Take ownership of moving solutions from prototype or development environments into stable, production-grade applications.
· Design and implement build, release, deployment, and rollback processes using CI/CD pipelines and modern DevOps practices.
· Work with cloud platforms and containerized environments to deploy, operate, monitor, and scale applications reliably.
· Implement appropriate logging, observability, exception handling, testing, security controls, and performance monitoring to support production operations.
· Partner with platform, infrastructure, security, and client IT teams to address environment setup, access, deployment, support, and operational-readiness requirements.
Backend, Data & Integration
· Design relational and/or NoSQL data models, application data flows, persistence layers, and integration patterns.
· Develop integrations with internal systems, third-party platforms, analytics services, and enterprise data sources using APIs, messaging, event-driven approaches, or batch interfaces.
· Apply sound engineering practices for authentication, authorization, API design, data validation, caching, error handling, and performance optimization.
Generative AI Engineering
· Contribute, where relevant, to the design and development of enterprise Generative AI capabilities using large language models (LLMs).
· Build or integrate agentic workflows and retrieval-augmented generation (RAG) solutions that ground model responses in enterprise data and knowledge sources.
· Apply embeddings and vector databases to support semantic search, retrieval, context management, and scalable GenAI application patterns.
Team Coaching & Engineering Quality
· Coach and mentor junior and mid-level engineers through design discussions, pair problem solving, code reviews, and development guidance.
· Help establish and reinforce engineering standards for architecture, coding practices, testing, documentation, version control, security, and release management.
· Break complex technical problems into manageable work packages and help the team execute with quality and discipline.
· Contribute to a strong engineering culture focused on ownership, pragmatic problem solving, continuous improvement, and delivery excellence.
Required Skills & Qualifications
Education
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
Experience
· 5-10 years of experience in full-stack development, software engineering, application engineering, or closely related roles.
· Strong track record of building and deploying production-grade web applications and backend services, not only prototypes or proofs of concept.
· Experience owning technical workstreams or projects and coordinating delivery across multiple contributors or functions.
· Experience mentoring developers, reviewing technical work, and providing hands-on engineering guidance.
· Demonstrated ability to work directly with business or client stakeholders and translate requirements into technical solutions.
Technical Skills
· Strong programming skills in Python and/or JavaScript/TypeScript.
· Hands-on experience with backend frameworks such as FastAPI, Flask, Django, Node.js, Express, or comparable technologies.
· Strong frontend development experience using React.js and modern UI development practices.
· Solid understanding of SQL databases such as PostgreSQL, MySQL, or SQL Server; familiarity with NoSQL databases is an advantage.
· Experience designing and integrating REST APIs, services, and authentication/authorization mechanisms.
· Hands-on experience with Git, automated testing, CI/CD pipelines, Docker, and cloud platforms such as Azure, AWS, or GCP.
· Good understanding of software architecture, design principles, debugging, code quality, secure development, and application performance.
· Practical experience with deployment, observability, monitoring, incident troubleshooting, and production support.
Preferred Qualifications
· Experience delivering software or analytics applications in oil & gas, energy, energy retail, utilities, or marketing analytics environments.
· Experience with microservices architecture, Kubernetes, distributed systems, messaging platforms, or event-driven architectures.
· Experience building data-intensive, analytics, optimization, or workflow-driven applications.
· Exposure to AI/ML or Generative AI application development, including integration of LLM-based capabilities into enterprise applications.
· Familiarity with GenAI technologies such as Azure OpenAI/OpenAI, LangChain, vector databases, or RAG architectures is useful but not required.
· Prior experience in consulting, client-facing delivery, technical project management, or engagement management is an advantage.
Key Competencies
· Strong engineering judgment and hands-on problem-solving ability
· Technical project ownership and delivery discipline
· Clear client communication and stakeholder management
· Ability to move comfortably between code-level detail and business-level discussions
· Ability to coach junior team members and raise overall engineering quality
· Strong ownership mindset with a practical, product-oriented approach
· Ability to manage ambiguity, priorities, dependencies, and delivery risks
