Forward Deployed AI Engineer – Senior/Principal Level

Cloudera

Full-stack ML engineer embedding with customers for AI/ML solutions. Collaborating to design and ship scalable applications while driving AI innovation with Cloudera.

Posted 7/30/2026full-timeRemote • Texas • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying production-grade AI/ML applications, with a strong focus on full-stack development, scalable solution architecture, and customer engagement. Proficient in LLMOps/MLOps practices and capable of mentoring teams while driving AI capabilities within enterprise environments.

Highest-signal resume keywords

Full-Stack AI/ML Application DevelopmentLLMOps/MLOps PracticesAI Solution Architecture DesignCustomer Engagement and Technical StrategyMentorship and Internal Enablement

ATS Keywords

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Hard Skills

Software EngineeringData EngineeringApplied AI/ML SkillsBuilding ML SystemsGenAI/Agentic ApplicationsFoundation ModelsContext EngineeringFine-TuningSemantic SearchRetrieval-Augmented Generation (RAG)

Soft Skills

Collaborative MindsetHigh AgencyMentorship

Certifications & Qualifications

BScMScPhD in Related Field

Industry Keywords

AI RoadmapsSolution DesignDeploymentEnterprise StandardsSecurityGovernanceCompliance

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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
Bsc/Msc/PhD in related field or equivalent experience

Benefits

Comp & perks

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