Generative AI Developer

Stantec•Austin, TX

16h

About The Position

Generative AI Developer Your Opportunity We are seeking a GenAI Developer to drive the design, maturation, and enterprise deployment of generative AI and agentic AI systems within Stantec’s Digital Center of Excellence (DCoE). This role will support a growing portfolio of AI initiatives across the organization, focusing on building scalable, secure, and well-governed solutions, including LLM-powered agents, multi-agent systems, retrieval-augmented generation (RAG), and intelligent automation platforms. You will work closely with data scientists, engineers, enterprise architects, and business stakeholders to define architectural patterns, establish technical standards, and guide the implementation of advanced GenAI capabilities. This position plays a critical role in shaping enterprise AI architecture, ensuring solutions are reliable, compliant, and aligned with Stantec’s governance, security, and responsible AI principles.

Requirements

Strong background designing and delivering modern cloud solutions, APIs, and data/AI platforms.
Demonstrated experience with GenAI solution patterns
Familiarity with security, privacy, and governance practices for enterprise AI solutions.
Ability to communicate complex concepts clearly to technical and non-technical audiences, influencing stakeholders through architecture guidance.
Experience partnering across disciplines in agile delivery environments.
Understanding application deployment, hosting, and scaling using the Azure App Service platform within Azure environments.
Master’s degree or higher degree in Computer Science, Engineering, or related field (or an equivalent combination of education and experience).
7+ years of professional experience in architecture, software engineering, data engineering, or AI/ML solution delivery, with recent hands-on GenAI solution experience.

Nice To Haves

Experience deploying AI/GenAI solutions in Azure environments, including familiarity with Azure AI Foundry and Databricks Mosaic AI, would be highly valued.

Responsibilities

Architect end-to-end GenAI solutions, including model lifecycle management, evaluation, deployment, and monitoring.
Partner with ML/AI leads and engineering teams to integrate LLMs, autonomous agents, and GenAI services into existing and new solution pipelines.
Act as a technical advisor and reviewer, supporting architectural decisions, code reviews, and design trade-offs.
Provide architectural guidance for production deployments using Azure-native services, Databricks, and Azure DevOps CI/CD pipelines, ensuring solutions align with enterprise standards.
Review and advise on infrastructure approaches, including containerization, orchestration, and infrastructure-as-code to ensure scalability, security, and operational readiness.
Collaborate with product owners, engineering, security, and data teams to design solutions that meet functional and non-functional requirements (performance, reliability, compliance, and cost).
Establish and enforce governance for model usage, prompt and tool management, safety controls, data handling, and lifecycle management.
Design integrations with enterprise data platforms, knowledge sources, and APIs, ensuring appropriate access controls and auditability.
Guide implementation teams through design reviews, technical decision-making, and delivery of best practices.
Document architectural patterns, methodologies, and lessons learned; contribute to internal knowledge bases and Communities of Practice.
Evaluate emerging GenAI technologies and recommend adoption strategies based on business value and risk.
Stay current with emerging research, tools, and frameworks in Generative AI, Agentic AI, and multi-agent systems.