Forward Deployed Engineer, AI/ML

RevStar

. Design, build, and deploy production-grade data pipelines, analytics engines, and Generative AI/LLM applications using Databricks, Spark, Python/PySpark, and modern cloud ecosystems .

Posted 9/24/2026contractRemote • Colombia, Mexico, Brazil, Argentina, Chile, VenezuelaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying data pipelines and analytics engines within the Databricks ecosystem, with a strong focus on Generative AI applications and cloud-native architectures. Proven ability to lead technical delivery for enterprise clients while mentoring junior team members and driving measurable business outcomes.

Highest-signal resume keywords

Data EngineeringDatabricks EcosystemCloud-Native ArchitecturesMachine LearningTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignAnalytics Engine DevelopmentGenerative AI ApplicationsRAG Pipeline DeploymentML Pipeline ManagementVector Database ManagementLegacy Platform MigrationModel Fine-TuningDatabricks WorkflowsSpark/PySpark

Soft Skills

Exceptional Communication SkillsClient Stakeholder ManagementMentoring

Tools & Technologies

DatabricksDelta LakeUnity CatalogMLflowAWSS3GlueLambdaRedshiftMosaic AI

Certifications & Qualifications

Databricks Certified Data Engineer ProfessionalDatabricks Certified Machine Learning Professional

Industry Keywords

HealthcareRetailConsumer GoodsEnterprise ClientsFortune 500

Tech Stack

Tools & technologies

Amazon RedshiftAWSCloudPySparkPythonSparkUnity

About the role

Key responsibilities & impact

Design, build, and deploy production-grade data pipelines, analytics engines, and Generative AI/LLM applications using Databricks, Spark, Python/PySpark, and modern cloud ecosystems
Serve as the primary technical leader on strategic enterprise client engagements
Partner with C-level executives, VP/Directors of Data, and engineering teams to translate business challenges into technical solutions
Lead complex legacy platform migrations onto the Databricks Lakehouse architecture
Guide enterprise customers in adopting GenAI solutions, RAG architectures, model fine-tuning, and MLflow/Databricks Mosaic AI integrations
Identify high-value technical use cases across client business units, expand Databricks platform usage, and drive measurable client ROI
Mentor junior Solution Engineers, Architects, and Consultants
Contribute to internal RevStar code libraries, reusable accelerators, and technical delivery best practices

Requirements

What you’ll need

5+ years of hands-on experience in Data Engineering, Machine Learning, or Solutions Architecture
3+ years of deep technical experience within the Databricks Ecosystem (Delta Lake, Unity Catalog, MLflow, Spark/PySpark, Databricks Workflows/Jobs, Mosaic AI)
Practical experience designing and deploying RAG pipelines, fine-tuning LLMs, working with vector databases, and managing ML pipelines end-to-end
Strong expertise in cloud-native architectures (AWS preferred—S3, Glue, Lambda, Redshift, etc.)
Proven track record of migrating enterprise legacy data warehouses/lakes onto Databricks
Databricks Certified Data Engineer Professional and/or Machine Learning Professional preferred
Demonstrated track record of leading technical delivery for Fortune 500 or large enterprise clients
Healthcare, Retail, or Consumer Goods experience is a strong plus
Exceptional verbal and written communication skills
Comfortable presenting technical architecture, building POCs/demos, and managing client stakeholders up to the C-suite
Ability to spot technical expansion opportunities within existing client accounts and serve as a technical advocate to grow account footprint

Benefits

Comp & perks

Independent Contractor (Form 1099-NEC)
Hourly rate, commensurate with experience