Robotics QA Automation Engineer

Description General Description We are looking for an innovative and detail-oriented Robotics Automation Specialist to join our team.
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In this role, you will work closely with Quality Specialists that have established rubrics and industry leading best practices for robotics data collection and annotation.
You will be responsible for translating them into designing, integrating, and managing workflows that connect multiple AI models, tools, and services with human-in-the-loop to deliver scalable, efficient, and business-aligned solutions.
The ideal candidate has strong technical expertise in AI/ML, experience with orchestration frameworks, and the ability to translate business needs into automated, AI-driven processes.
This position requires a blend of engineering, problem-solving, and strategic thinking to ensure that Robotics initiatives are effectively deployed, optimized, and continuously improved.
Key Responsibilities: Previous experience with high quality egocentric data collection and annotation pipelines from Automation and HITL perspectives Design and implement orchestration pipelines that connect multiple GenAI models, APIs, and tools into end-to-end workflows.
Collaborate with data scientists, engineers, and business stakeholders to define use cases and translate them into orchestrated AI solutions.
Ensure system scalability, performance, and reliability through effective orchestration strategies.
Monitor and optimize AI pipelines, addressing bottlenecks, errors, and inefficiencies.
Integrate orchestration platforms with cloud environments and enterprise systems.
Establish best practices for AI orchestration, versioning, monitoring, and lifecycle management.
Document processes, technical architectures, and orchestration standards for knowledge sharing.
Stay updated on advancements in AI orchestration, LLMs, and automation tools to continuously enhance solutions.
Requirements Education: Bachelor’s or Master’s Degree in Computer Science, Data Engineering, Artificial Intelligence, or related field (or equivalent experience).
Experience: 3 years of experience in AI/ML engineering, data engineering, or workflow orchestration.
Experience in GenAI/LLM orchestration is a strong plus.
Skills: Proficiency with orchestration tools/frameworks (e.g., Airflow, Prefect, LangChain, Dagster, Kubeflow, or similar).
Strong programming skills (Python preferred) for building and integrating orchestration pipelines.
Familiarity with Generative AI models (e.g., LLMs, diffusion models) and their deployment.
Knowledge of cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
Strong problem-solving and analytical skills to optimize workflows.
Excellent communication and collaboration skills to work across technical and non-technical teams.
Ability to balance innovation with reliability and compliance considerations.
About Company: TELUS Digital is the customer experience transformation partner to the world's most admired brands.
Our diverse team weaves data, technology, and human ingenuity to deliver differentiated customer journeys, drive operational effectiveness, and scale AI solutions with meaningful value and positive impact.
We craft real-world solutions in the moments that matter, from customer acquisition to lifelong loyalty.
Enabled by our global reach
- spanning 78,000 experts in 33 countries
- and deep industry expertise, we help over 600 organizations make the customer experience feel effortless.
Our solutions span Data & AI, Digital Experience & IT, CX Management and Trust & Safety.
At the core of our innovation is Fuel iX™, an enterprise-grade generative AI platform that helps clients safely access and optimize leading LLMs to scale their own AI from pilot to production.
Equal Opportunity Employer Statement At TELUS Digital, we are proud to be an equal opportunity employer and are committed to creating a diverse and inclusive workplace. xsxvtuf
All aspects of employment, including the decision to hire and promote, are based on applicant's qualifications, merits, competence and performance without regard to any characteristic related to diversity.