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Temporary Open Ai Jobs (NOW HIRING)

Real Soft, Inc.

AI Architect

Winchester Center, CT · On-site

$61 - $80.25/hr

Temp to perm for the right candidate. WM-Data and Application Architect - Overview The Wealth ... Foundry, Claude, Open AI • Security and identity frameworks Domain Expertise • Deep ...

TALENT Software Services

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AI Data and Application Architect - Wealth Management

New York, NY · On-site

$80 - $92/hr

Remote Duration: 3 months, temp-to-perm for the right candidate Overview The role is responsible ... AI Technologies - Azure Foundry, Claude, Open AI. * Security and identity frameworks. * Domain ...

NTT DATA Services

Applied AI Researcher

Jersey City, NJ · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Publications, patents, internal research contributions, open-source AI contributions, or prior ... If the position offered in temporary, the position will not be eligible for incentive compensation.

NTT DATA Services

Applied AI Researcher

Jersey City, NJ

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Publications, patents, internal research contributions, open-source AI contributions, or prior ... If the position offered in temporary, the position will not be eligible for incentive compensation.

NTT DATA Services

Applied AI Researcher

Jersey City, NJ

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Publications, patents, internal research contributions, open-source AI contributions, or prior ... If the position offered in temporary, the position will not be eligible for incentive compensation.

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Temporary Open Ai information

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How much do temporary open ai jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for temporary open ai in the United States is $18.38, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $19.95 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a temporary OpenAI engineer, and why are they important?

To thrive as a Temporary OpenAI Engineer, you need a strong background in computer science, machine learning, and programming, typically supported by a relevant degree and experience with AI development. Familiarity with tools like Python, TensorFlow or PyTorch, and cloud platforms is commonly required, along with knowledge of version control systems like Git. Strong problem-solving skills, adaptability, and effective communication help you excel in a fast-paced, collaborative R&D environment. These skills ensure you can contribute to innovative AI projects, adapt to evolving technologies, and work efficiently within dynamic teams.

What is the difference between Temporary Open Ai vs Data Analyst?

AspectTemporary Open AiData Analyst
Required CredentialsOften no formal degree required; familiarity with AI toolsBachelor's degree in data science, statistics, or related field
Work EnvironmentProject-based, flexible, often remoteOffice or remote, structured work hours
Employer & Industry UsageTech companies, startups, AI-focused projectsBusiness, finance, healthcare, and various industries
Common Search & ComparisonTemporary Open Ai vs Data AnalystSimilar roles in data-driven industries

Temporary Open Ai roles focus on short-term AI project support, requiring familiarity with AI tools and flexible work settings. Data Analysts analyze data to inform business decisions, often with formal education. While both roles involve data, Temporary Open Ai is more specialized in AI applications, whereas Data Analysts have broader data analysis responsibilities.

What is a temporary Open AI job?

Temporary Open AI jobs are short-term positions offered by OpenAI or related organizations to support specific projects, research initiatives, or operational needs. These roles may include research assistants, software engineers, data annotators, or project managers, and typically last for a defined period, such as a few months. Temporary positions provide opportunities to work with cutting-edge artificial intelligence technologies and gain valuable experience, often with the possibility of transitioning to a permanent role. Candidates are usually expected to have relevant technical or research skills, and the work environment is fast-paced and collaborative.

What are some common challenges when working in a temporary AI role, and how can I prepare for them?

In a temporary AI position, one common challenge is quickly adapting to existing projects and workflows, as you'll often be expected to contribute immediately with minimal onboarding. You may also face tight deadlines and the need to rapidly learn new tools or data sets specific to the company. To prepare, familiarize yourself with common AI frameworks, maintain strong communication with team members, and be proactive in seeking clarification on project requirements. Flexibility and a willingness to learn are key to thriving in this fast-paced, dynamic environment.

What cities are hiring for Temporary Open Ai jobs?

Cities with the most Temporary Open Ai job openings:

What are the most commonly searched types of Open Ai jobs?

The most popular types of Open Ai jobs are:

What states have the most Temporary Open Ai jobs?

States with the most job openings for Temporary Open Ai jobs include:

What job categories do people searching Temporary Open Ai jobs look for?

The top searched job categories for Temporary Open Ai jobs are:

Temporary Open Ai jobs near you
Infographic showing various Temporary Open Ai job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, and 3% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $38,238 per year, or $18.4 per hour.

AI Architect

Real Soft, Inc.

Winchester Center, CT • On-site

$61 - $80.25/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Temp to perm for the right candidate.
WM-Data and Application Architect - Job Description
Overview
The Wealth Management Solution Architect is responsible for designing and delivering end-to-end technology solutions that support wealth advisory, client engagement, portfolio management, and operational efficiency. This role partners with business and technology stakeholders to translate strategic objectives into scalable, secure, and compliant architectures across the wealth management ecosystem.
Key Responsibilities
1. Solution Architecture & Design
• Define end-to-end solution architectures for wealth management platforms, including advisor tools, client portals, and operational systems.
• Develop architecture blueprints, reference patterns, and roadmaps aligned with enterprise standards.
• Ensure solutions are scalable, resilient, secure, and cloud enabled.
2. Wealth Management Platform Integration
• Architect integrations across:
o CRM platforms (e.g., Salesforce FSC)
o Knowledgeable of integration patterns and solution designs including synchronous/asynchronous Web API, Graph API, API Gateways/Management, Messaging, and Event based architectures and streaming technologies.
o Portfolio management and trading systems
o Financial planning tools
o Client onboarding/KYC platforms
• Enable seamless data flow across front, middle, and back-office systems.
3. Digital & Client Experience Enablement
• Design solutions supporting omnichannel client engagement (web, mobile, Conversational AI, advisor-assisted).
• Enable personalized client experiences through data-driven insights.
• Support modernization of advisor desktop and digital workplace tools.
4. Data & Analytics Architecture
• Define architecture for:
o Client data platforms and 360° views
o Investment analytics and reporting
o Data governance and lineage
• Collaborate with data teams on data lakes, warehouses, and real-time data streaming using Databricks, Snowflake, and Azure Data Fabric to build scalable and reusable solutions.
o Define patterns for:
• Data quality, lineage, and governance
• Data partitioning, performance optimization, and cost efficiency
5. AI, Automation & Innovation
• Integrate AI/ML capabilities:
o Advisor assist (Copilot, recommendations)
o Predictive analytics (client segmentation, next-best action)
o Document automation and workflow orchestration
• Identify and drive automation opportunities across wealth operations.
• Collaborate with business and technical stakeholders to translate real-world research and workflow needs into AI-powered solutions that are measurable, reliable, and safe in production.
• Knowledge of multi-agent workflows (planner/supervisor + specialist agents) with explicit state management and routing, and interoperability via emerging agent protocols (MCP for tool integration, A2A for agent-to-agent delegation) designed for non-deterministic behavior and real operational constraints.
6. Security, Risk & Compliance
• Ensure adherence to financial services regulations (SEC, FINRA, GDPR).
• Incorporate data privacy, cybersecurity, and identity/access controls in all solutions.
• Partner with risk and compliance teams on governance
• Knowledge, background, understanding of fundamental security concepts including data encryption, AuthN/AuthZ, SSO, and managed identities.
7. Delivery Oversight & Governance
• Provide architecture oversight across programs and projects.
• Participate in Architecture Review Boards (ARB), ARC, and design reviews.
• Ensure adherence to enterprise architecture standards and best practices.
8. Technology Ecosystem & Integration
• Define integration approaches using:
o APIs and microservices
o Event-driven architecture
o Middleware and integration platforms
• Align solutions with cloud strategy (Azure/AWS), DevSecOps, and platform engineering.
Required Qualifications
Education & Experience
• Bachelor's or Master's degree in Computer Science, Engineering, Finance, or related field
• 10+ years of experience in solution or enterprise architecture
• Proven experience in wealth management or financial services domain
Technical Expertise
• CRM platforms (Salesforce Financial Services Cloud preferred)
• Cloud platforms (Azure preferred; AWS/GCP acceptable)
• API/microservices architecture and integration patterns
• Data platforms (data lake-Databricks, warehouse, real-time streaming)
• AI Technologies - Azure Foundry, Claude, Open AI
• Security and identity frameworks
Domain Expertise
• Deep understanding of:
o Wealth advisory lifecycle
o Retirement lifecycle
o Investment products (equities, fixed income, mutual funds, annuities)
o Client onboarding, servicing, and reporting workflows
Preferred Qualifications
• Experience with AI/GenAI solutions (Copilot, NLP, recommendation engines)
• Familiarity with advisor workstation modernization and digital workplace tools
• Knowledge of contact center platforms (e.g., Genesys)
• Industry certifications (TOGAF, Azure Architect, etc.)
Key Competencies
• Strategic and systems thinking
• Strong stakeholder engagement and executive communication
• Business-technology alignment
• Innovation mindset with focus on AI and automation
• Problem-solving and decision-making

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