

Contract on W2 Only :: AIML Senior Platform Support Engineer β Vector/LLDS Database & AI Platform Focus -- Charlotte, NC & Irving, TX (Onsite)
β - Featured Role | Apply direct with Data Freelance Hub
This role is a long-term contract for an AIML Senior Platform Support Engineer focused on Vector/LLDS Database & AI Platform in Charlotte, NC & Irving, TX. Requires expertise in Elasticsearch, Linux, Python, and big data technologies, with production AI support experience.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
-
ποΈ - Date discovered
September 18, 2025
π - Project duration
Unknown
-
ποΈ - Location type
On-site
-
π - Contract type
W2 Contractor
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π - Security clearance
Unknown
-
π - Location detailed
Irving, TX
-
π§ - Skills detailed
#Kubernetes #Monitoring #Databases #Splunk #AI (Artificial Intelligence) #Scripting #Debugging #Elasticsearch #GCP (Google Cloud Platform) #Automation #Deployment #Indexing #Observability #Data Exploration #Disaster Recovery #Python #Azure #Big Data #Docker #Shell Scripting #Cloud #Programming #Grafana #Data Science #Hadoop #Data Pipeline #Linux #Data Ingestion
Role description
Hi ,
Hope you are doing great!
We have the below urgent position with my client. Please reply if you are interested.
Job Title: AIML Senior Platform Support Engineer β Vector/LLDS Database & AI Platform Focus
Location : Charlotte, NC & Irving, TX (Onsite)
Long Term Contract
Core Technical Skills
β’ Vector Databases: Hands-on experience with Elasticsearch or similar; understanding of similarity search, indexing strategies, and embedding management.
β’ Linux Systems: Strong command-line skills; shell scripting; system-level monitoring and debugging.
β’ Python Programming: Proficient in automation scripting; experience in building AI models, data pipelines, and OpenAI integrations.
β’ Big Data Technologies: Familiarity with Hadoop-based platforms like MapR and Hortonworks.
AI Platform & Production Support
β’ Experience supporting predictive AI workloads in production.
β’ Troubleshooting across data ingestion, model inference, and deployment layers.
β’ Familiarity with CI/CD pipelines and containerization (Docker, Kubernetes).
β’ On-call support for GenAI and predictive pipelines (1 week every 6β8 weeks).
β’ Understanding of enterprise disaster recovery (DR) solutions including backup and restore.
Observability & Monitoring
β’ Ability to define and implement observability strategies for AI systems.
β’ Experience with tools such as Splunk, Grafana, ELK stack, OpenTelemetry.
β’ Proactive monitoring of model failures, latency, and system health.
Bonus Qualifications
β’ Multi-cloud Experience: Exposure to GCP and Azure environments.
β’ Data Science Lifecycle: Involvement in full-cycle projects including problem definition, data exploration, modeling, evaluation, training, scoring, and operationalization.
β’ MLOps Principles: Understanding of model lifecycle management and collaboration with data scientists to deploy solutions.
Thanks, and Regards
Saurabh Kumar | Lead Recruiter
saurabh.yadav@ampstek.com | www.ampstek.com
https://www.linkedin.com/in/saurabh-kumar-yadav-518927a8/
Call to : +1 609-360-2671
Hi ,
Hope you are doing great!
We have the below urgent position with my client. Please reply if you are interested.
Job Title: AIML Senior Platform Support Engineer β Vector/LLDS Database & AI Platform Focus
Location : Charlotte, NC & Irving, TX (Onsite)
Long Term Contract
Core Technical Skills
β’ Vector Databases: Hands-on experience with Elasticsearch or similar; understanding of similarity search, indexing strategies, and embedding management.
β’ Linux Systems: Strong command-line skills; shell scripting; system-level monitoring and debugging.
β’ Python Programming: Proficient in automation scripting; experience in building AI models, data pipelines, and OpenAI integrations.
β’ Big Data Technologies: Familiarity with Hadoop-based platforms like MapR and Hortonworks.
AI Platform & Production Support
β’ Experience supporting predictive AI workloads in production.
β’ Troubleshooting across data ingestion, model inference, and deployment layers.
β’ Familiarity with CI/CD pipelines and containerization (Docker, Kubernetes).
β’ On-call support for GenAI and predictive pipelines (1 week every 6β8 weeks).
β’ Understanding of enterprise disaster recovery (DR) solutions including backup and restore.
Observability & Monitoring
β’ Ability to define and implement observability strategies for AI systems.
β’ Experience with tools such as Splunk, Grafana, ELK stack, OpenTelemetry.
β’ Proactive monitoring of model failures, latency, and system health.
Bonus Qualifications
β’ Multi-cloud Experience: Exposure to GCP and Azure environments.
β’ Data Science Lifecycle: Involvement in full-cycle projects including problem definition, data exploration, modeling, evaluation, training, scoring, and operationalization.
β’ MLOps Principles: Understanding of model lifecycle management and collaboration with data scientists to deploy solutions.
Thanks, and Regards
Saurabh Kumar | Lead Recruiter
saurabh.yadav@ampstek.com | www.ampstek.com
https://www.linkedin.com/in/saurabh-kumar-yadav-518927a8/
Call to : +1 609-360-2671