Forward Deployed AI Engineer, Australia (Senior/Principal Level)
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Before you apply
Location2 Locations
Work moderemote · United States
Typefull-time
SenioritySenior
Experience7+ yrs
DepartmentCorp. Strategy
Company size1,001–5,000 people
PostedAug 12, 2026 · 2mo ago
Verified live5d ago
At a glanceSummarised by Seekless from the posting.
7+ years of experience building and deploying production-grade systems, including 2-4 years experience building ML systems or GenAI/agentic applications
Strong hands-on software engineering, data engineering, and applied AI/ML skills, with experience building full-stack ML applications or agentic systems using modern AI frameworks and tooling
Experience with foundation models, context engineering, fine-tuning, semantic search, Retrieval-Augmented Generation (RAG), and agentic workflows
Deep understanding of LLMOps/MLOps practices including evaluation, observability, serving, monitoring, and lifecycle management
Experience designing and implementing scalable AI solution architectures aligned to enterprise standards (security, governance, compliance, etc.)
The ability to engage directly with customers, both technical and executive audiences - to translate needs into actionable technical strategy
High agency with the ability to operate autonomously and thrive in ambiguous, fast-moving customer environments
A collaborative mindset and passion for enabling others through mentorship, internal enablement, or reusable tooling
Experience with cloud technologies (AWS, Azure, GCP)
Experience using the Cloudera platform
Experience with open source big data technologies like Spark, Iceberg, NiFi, etc
Experience with AI infrastructure and runtime technologies including NVIDIA GPUs, inference optimization, model serving, or distributed AI workloads
Skills
AI
ML
GenAI
agentic systems
foundation models
context engineering
fine-tuning
semantic search
Retrieval-Augmented Generation (RAG)
agentic workflows
LLMOps
MLOps
AWS
Azure
GCP
Cloudera platform
Spark
Iceberg
NiFi
NVIDIA GPUs
inference optimization
Benefits
Generous PTO policy
Unplugged days
Flexible wfh policy
Mental & physical wellness programs
Phone and internet reimbursement program
Access to continued career development
Comprehensive benefits and competitive packages
Paid volunteer time
Employee resource groups
Business Area:
Corp. Strategy
Seniority Level:
Mid-Senior level
Job Description:
At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we’re the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.
About Forward Deployed Engineering (FDE) at Cloudera
About the role
Cloudera’s Forward Deployed Engineering (FDE) function sits within the Applied AI organization, and is a specialized AI/ML engineering team focused on accelerating AI adoption within our most strategic enterprise customers. We embed directly with customers to rapidly pilot AI use cases, solve real-world business challenges, and help operationalize advanced AI capabilities within enterprise environments.
Cloudera FDEs operate at the intersection of customer engineering, AI innovation, and enterprise deployment - driving high-impact AI outcomes for customers and codifying solution patterns for repeatable delivery at scale.
About the role
Cloudera is looking for a seasoned full-stack ML engineer who can embed with customers to design technical use cases, and ship scalable enterprise AI/ML solutions on Cloudera.
As a Forward Deployed AI Engineer, you will:
•
Build & Prototype AI Apps - Develop full-stack AI/ML applications on Cloudera to demonstrate how AI and agentic systems solve real enterprise use cases
•
Partner with Strategic Customers - Work directly with customer teams to drive AI and agentic use cases from early prototype toward production readiness
•
Shape Enterprise AI Architecture - Advise customer leaders on AI roadmaps, solution design, deployment, and AI use cases
•
Codify Solution Patterns - Standardize successful patterns into repeatable reference architectures, productized solutions, starter kits, and internal playbooks
•
Multiply impact - Be a thought leader, mentor Cloudera teams, and contribute to resources that grow our AI capability. Channel field and customer signal back to Product teams to improve our AI platform and products
We are excited if you have:
•
7+ years of experience building and deploying production-grade systems, including 2-4 years experience building ML systems or GenAI/agentic applications
•
Strong hands-on software engineering, data engineering, and applied AI/ML skills, with experience building full-stack ML applications or agentic systems using modern AI frameworks and tooling
•
Experience with foundation models, context engineering, fine-tuning, semantic search, Retrieval-Augmented Generation (RAG), and agentic workflows
•
Deep understanding of LLMOps/MLOps practices including evaluation, observability, serving, monitoring, and lifecycle management
•
Experience designing and implementing scalable AI solution architectures aligned to enterprise standards (security, governance, compliance, etc.)
•
The ability to engage directly with customers, both technical and executive audiences - to translate needs into actionable technical strategy
•
High agency with the ability to operate autonomously and thrive in ambiguous, fast-moving customer environments
•
A collaborative mindset and passion for enabling others through mentorship, internal enablement, or reusable tooling
You may also have:
•
Experience with cloud technologies (AWS, Azure, GCP)
•
Experience using the Cloudera platform
•
Experience with open source big data technologies like Spark, Iceberg, NiFi, etc
•
Experience with AI infrastructure and runtime technologies including NVIDIA GPUs, inference optimization, model serving, or distributed AI workloads
What you can expect from us:
•
Generous PTO Policy
•
Support work life balance with Unplugged Days
•
Flexible WFH Policy
•
Mental & Physical Wellness programs
•
Phone and Internet Reimbursement program
•
Access to Continued Career Development
•
Comprehensive Benefits and Competitive Packages
•
Paid Volunteer Time
•
Employee Resource Groups
Legal
EEO/VEVRAA