Senior Engineer – AI

Dayforce

Senior AI Engineer designing, building, and operationalising AI solutions at LAB3 for enterprise clients. Working across the AI lifecycle from prototyping to production.

Posted 7/29/2026full-timeRemote • 🇦🇺 AustraliaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in delivering Agentic AI and GenAI workloads on Azure, with a strong focus on MLOps, CI/CD practices, and enterprise-grade security. Proven ability to lead technical workshops, mentor engineers, and collaborate across teams to develop scalable AI solutions.

Highest-signal resume keywords

Agentic AI ExperienceAzure ML ExpertiseMLOps ImplementationTechnical LeadershipCI/CD Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringData EngineeringAI EngineeringRAG Pipeline DevelopmentPrompt OptimizationModel MonitoringExperiment TrackingFeature Store ManagementInfrastructure as Code (IaC)Enterprise Search Solutions

Soft Skills

MentoringCross-Team CollaborationStakeholder Presentation

Tools & Technologies

AzureDatabricksAzure MLADLSDelta LakeEventHubSynapse/FabricAPIsVector DatabasesOperational Telemetry

Certifications & Qualifications

Azure CertificationDatabricks Certification

Industry Keywords

Agentic AIGenAIEnterprise SearchResponsible AIOperational Monitoring

Tech Stack

Tools & technologies

Azure

About the role

Key responsibilities & impact

Work with clients to understand requirements, shape technical solutions, and deliver Agentic AI and GenAI workloads on Azure.
Build production-grade applications with CI/CD, monitoring, and observability.
Develop robust RAG pipelines, optimise prompts, improve latency/cost, and design evaluation/test frameworks for LLM-based systems.
Implement MLOps with Azure ML/Databricks including experiment tracking, model registry, feature stores, automated deployment, and IaC .
Establish operational telemetry and model monitoring (drift, bias, quality).
Work with data engineers across ADLS, Delta Lake, EventHub, Synapse/Fabric, APIs, and vector databases to enable scalable hybrid retrieval architectures.
Apply enterprise-grade security (Entra, networking, secrets, RBAC), embed responsible AI practices, and produce HLD/LLDs.
Lead workshops, present to stakeholders, mentor engineers, and contribute to reusable components and accelerators.

Requirements

What you’ll need

7–10+ years in software/data/AI engineering, including 1 year in Agentic AI.
Experience delivering enterprise Search/RAG/virtual agent solutions on Azure.
Strong hands-on skills with Azure, Databricks, and Azure ML.
Proven technical leadership, mentoring, and cross-team collaboration.
Preferably: code/design artefacts, Azure/Databricks certifications, or related academic background.

Benefits

Comp & perks

Work with a Microsoft Partner of the Year award winner with multiple specialisations
Be supported by experienced peers and leaders that value technical expertise and encourages innovation, with clear career pathways and ongoing learning
Enjoy a supportive workplace that promotes inclusion, flexibility, diversity, and celebrates differences.
Take advantage of largely working from home in our remote/hybrid workplace and enjoy the flexibility to balance your life
Be part of a team that leverages modern technologies to solve real problems and provides top level of customer satisfaction