Job Details
Cloud Platform Engineer - AI, Analytics & Data Science
Primary Skills
Job Description
Client: FINRA
Pay Rate: $60/Hr on C2C
Pv Note :
The client requires an assessment round before profile submission. Candidates must complete the assessment independently without using AI tools or any external assistance. Any use of AI tools during the assessment may be detected and result in disqualification.
Job Details:
Visa : Apart from OPT/CPT, we are good to submit the rest.
Job ID: 26-02247
Title: Cloud Platform Engineer – AI, Analytics & Data Science
Location: Washington, DC / Rockville, MD / McLean, VA (Hybrid – 3 days onsite with 2 days remote)
Duration: 6 Months with possible extension
Interview process: Phone, Onsite panel
Job Summary:
We are seeking an experienced and versatile Cloud Platform Engineer to support and enhance enterprise analytics, artificial intelligence, and data science platforms.
The ideal candidate will have a broad technical background spanning AWS cloud infrastructure, Kubernetes, software integration, data engineering, and AI/ML technologies. This role requires an engineer who can support the full lifecycle of enterprise platforms, from infrastructure administration and system integration to troubleshooting, optimization, and end-user support.
The successful candidate will be a strong problem solver who is adaptable, eager to learn new technologies, and comfortable collaborating with geographically distributed teams.
Key Responsibilities
Administer, maintain, and optimize cloud-based analytics, AI, and data science platforms within AWS environments.
Manage Kubernetes-based infrastructure to ensure platform reliability, scalability, and performance.
Develop and maintain integrations with identity providers, enterprise data sources, and third-party systems.
Support data science and data engineering workflows, including data processing, model development, and deployment.
Work with enterprise AI/ML platforms such as Dataiku, Domino, and Amazon SageMaker Unified Studio.
Support generative AI initiatives, machine learning model development, and related platform capabilities.
Troubleshoot complex technical issues across infrastructure, applications, integrations, and user environments.
Provide technical support to platform users, including data scientists, engineers, and other technical stakeholders.
Collaborate with cross-functional and geographically distributed teams to implement platform enhancements and resolve technical challenges.
Identify opportunities to improve platform automation, operational efficiency, and overall user experience.
Required Qualifications
Strong experience with AWS cloud infrastructure and system administration.
Hands-on experience with Kubernetes and containerized environments.
Experience supporting enterprise software platforms and developing system integrations.
Understanding of identity management, data source connectivity, APIs, and system plugins.
Familiarity with data science, data engineering, and AI/ML workflows.
Strong troubleshooting, analytical, and problem-solving skills.
Ability to quickly learn and adapt to new technologies and platforms.
Excellent communication and collaboration skills, particularly within distributed teams.
Preferred Qualifications
Experience with Dataiku, Domino, Amazon SageMaker, or comparable enterprise AI/ML platforms.
Familiarity with generative AI, machine learning model development, and MLOps practices.
Experience with cloud automation, infrastructure management, and platform monitoring.
Knowledge of data pipelines, data integration, and enterprise data architectures.
Experience supporting technical users in complex, enterprise-scale environments.