Overview
Remote
Depends on Experience
Accepts corp to corp applications
Contract - W2
No Travel Required
Skills
API
Amazon Web Services
Artificial Intelligence
Auditing
Cloud Computing
Collaboration
Communication
Conflict Resolution
Data Security
Database
Deep Learning
DevOps
Good Clinical Practice
Google Cloud Platform
High Availability
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Microsoft Azure
Microsoft SSIS
Migration
Natural Language Processing
Problem Solving
Process Engineering
Provisioning
Python
Quality Assurance
Scalability
Scripting
Terraform
Virtual Machines
Workflow
Job Details
Job Title: AI Platform Engineers
Location: Remote
Type: Contract
Key Responsibilities:
- Design, develop, and maintain scalable AI infrastructure and services.
- Integrate OpenAI models (e.g., ChatGPT) into enterprise applications and workflows.
- Collaborate with data scientists and product teams to deploy and optimize AI solutions.
- Ensure platform reliability, performance, and security across AI deployments.
- Monitor and troubleshoot production AI systems, ensuring high availability and responsiveness.
Required Qualifications:
- Proven experience with OpenAI APIs and ChatGPT integration.
- Strong programming skills in Python and familiarity with cloud platforms (Azure, AWS, or Google Cloud Platform).
- Experience with MLOps tools and frameworks.
- Solid understanding of NLP, machine learning, and deep learning concepts.
- Excellent problem-solving and communication skills.
Additional details of day to day responsibilities.
- AZURE AI Services
- Simplify scalability of Applications.
- Automate the creation and provisioning of VMs.
- Automate process engineering as per client needs.
- Analyze data Security.
- Simplify workflow automation.
- Automation and Cost Saving Measures
- Adoption of Terraform scripting tool for various automation possibilities based on Client standards and guidelines.
- Automation for database activities like scheduled / recurring DB Refreshes as per requests from Application teams / Squads.
- Automation for other activities like DB masking as per Client guidelines.
- Use tools like Turbonomic to track and minimize azure consumption.
- Conduct weekly audit of database usage and decommission underutilized databases.
- Automated DB Access provisioning.
- Support all Modernization s efforts initiated by corresponding Dev / QA teams, if any:
- SSIS migration to newer technologies along with automation in the pipeline. Shift-left approach.
- Self-healing should be part of the development script. Develop toward No Ops.
- Transactional monitoring.
- Deployment through DevOps.
- API-based architecture.
- Parallelism should be part of development.
- Incorporate Workload identity.
- Automate development using CoPilot.
- Application E2E/Container effort.
Thanks and Regards
Sanket Parate
Talent Acquisition Specialist, KTEK Resourcing
Email -
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