AI Technical Capability Owner ( MLflow, AI/ML, GenAI,AWS)

  • Posted 2 hours ago | Updated 1 hour ago

Overview

Remote
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 12 Month(s)
No Travel Required

Skills

MLflow
AI/ML
GenAI
AWS

Job Details

Hello,    

 

Zenosys is looking AI Technical Capability Owner client Remote Work (If you are available and interested in the below opportunity, please send me updated resume. Thanks

 

 

Job Title AI Technical Capability Owner

Location- Remote Work

Duration –12+ Months Contracts Highly Chance to Extend 

 

 

  

 

 

 

If you are interested, please provide the following details along with the updated resume to speed up the interview process.

 

Full Legal Name as mentioned in Drivers' license:

Current Location:

Willing to relocate to the specified work location:

Currently on a project or actively looking:

Availability for interview:

Availability to join the project:

Date of Birth (Month/Date):

Visa Status:

Since how long the candidate has been in US

Need Education details with University Name, Location & Passing year in resume.:

LinkedIn address

 

What You'll Do

  • Own the technical capability roadmap for the AI/ML CoE and align with the Business Capability Owner on outcomes, funding, chargeback model, governance, and adoption plans
  • Translate company goals into technical guardrails, accelerators, and “opinionated defaults” for AI/ML delivery
  • Design and maintain end-to-end reference architectures on AWS and Databricks, including batch/streaming, feature stores, training/serving, and GenAI patterns
  • Publish reusable blueprints such as modules, templates, starter repositories, and CI/CD pipelines tailored for various personas like Data Scientists, ML Engineers, and Citizen AI/ML Developers
  • Curate a suite of best-fit tools for data, ML, GenAI, and MLOps (e.g., Databricks Lakehouse, AWS S3, Bedrock for GenAI)
  • Conduct evaluations, POCs, and vendor assessments to set selection criteria, SLAs, and TCO models
  • Define technical guardrails for data security, lineage, access control, PII handling, and model risk management according to  AI Policy
  • Establish standards for experiment tracking, model registry, approvals, monitoring, and incident response
  • Lead workshops, organize engineering guilds, and deliver “train-the-trainer” programs.
  • Develop hands-on labs, documentation, and internal courses to upskill teams on AI/ML frameworks and tools

What You'll Need

Required:

  • 8–12+ years of experience in data/ML platform engineering or ML architecture, with 3+ years designing solutions on AWS and Databricks at enterprise scale
  • Proven expertise in defining reference architectures, golden paths, and reusable accelerators
  • MLOps experience including experiment tracking (MLflow), CI/CD pipelines, feature stores, model serving, observability, drift/quality monitoring, and A/B or shadow testing
  • Proficiency in GenAI patterns such as retrieval-augmented generation (RAG), vector search, prompt orchestration, and safety guardrails
  • Security-by-design mindset with experience in IAM/KMS, network segmentation, data classification, and compliance frameworks
  • Strong skills in organizing large groups (guilds, communities of practice, workshops) and influencing without authority
  • Exceptional presentation and communication skills for both technical and executive audiences

 

If interested Please send me your resume at 

 

Thanks,
HemendraKalal, 
Ph: (O)
Sr. Technical Recruiter, 
Fax:
Zenosys Consulting, 
Web: 

 

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