Generative AI Specialist

Worldwide Technology is looking for a Generative AI Specialist. This role is part of WWT s Strategic Resourcing services and is a contract role. The candidate will be supporting a WWT customer and will be employed by one of WWT s preferred partners. The partner will provide full compensation and benefit information prior to employment with the partner.

Company Overview:
Based in St. Louis, WWT works closely with industry leaders such as Cisco, HPE, Dell EMC, NetApp, VMware, Intel, AWS, Microsoft, and F5, focusing on three market segments: Fortune 500 companies, service providers and the public sector. WWT employs more than 5,400 people and operates in more than 2+ million square feet of state-of-the-art warehousing, distribution and integration space strategically located throughout the world. WWT is proud to announce that it has been named on the FORTUNE "100 Best Places to Work For " list for the eighth consecutive year and was awarded for multiple categories on Glassdoor's 2019 Employees' Choice Awards, honoring the Best Places to Work.

Title: Generative AI Specialist Strategic Engagement

Location: On-site at NYC/NJ (preferred location)

Duration/Type of Job: 12 months

Rate/Salary: A reasonable estimate of the current pay range for this position is $60 to $100 hourly (Rate range is on C2C basis). Actual pay will be based on a variety of factors, including shift, location, experience, skill set, performance, licensure and certification, and business needs, and will be set by your employer. The range for this position in other geographic locations may differ. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions, that is not included in base pay.

Role Overview:

Seeking a GenAI Platform Specialist to lead a strategic engagement focused on enabling enterprise-scale GenAI application development. The specialists will directly collaborate with technical teams to build robust GenAI platform capabilities, ensuring readiness at the application layer and maximizing ROI on GPU infrastructure.

The ideal candidate will possess both strategic architectural experience and hands-on implementation skills, with deep expertise in GenAI technologies, platform engineering, and developer enablement.

Key Responsibilities:

Platform Architecture & Design

• - Develop scalable reference architectures for GenAI applications.
• - Define reusable design patterns and workload distribution strategies.
• - Build proof-of-concept implementations to validate platform architecture.

Developer Tooling & Enablement

• - Design developer toolkits and libraries for GenAI development.
• - Build standardized APIs for LLM interactions and operations.
• - Create accelerators, templates, and documentation for fast prototyping.

LLM Engineering Best Practices

• - Design evaluation frameworks for model performance and quality.
• - Implement prompt management and optimization strategies.
• - Establish best practices for model selection, fine-tuning, and QA workflows.

Governance & Compliance

• - Adapt existing regulatory frameworks to GenAI use cases.
• - Build model risk management processes and audit trail capabilities.
• - Create documentation templates for compliance and oversight.

Performance & Cost Optimization

• - Define GPU resource optimization strategies for multi-tenant environments.
• - Create performance benchmarking, monitoring, and cost management tools.
• - Design optimization strategies tailored to specific workloads.

Production Operations & Deployment

• - Build production-ready deployment pipelines for LLM applications.
• - Define observability, monitoring, and incident response standards.
• - Create runbooks and enterprise integration frameworks.

Key Support Activities:

• - Production-ready GenAI platform components and tools.
• - Reference implementations and documented architectural patterns.
• - Standardized developer toolkits, templates, and libraries.
• - Evaluation and compliance frameworks aligned with company policies.
• - Collaborative code and technical documentation for knowledge transfer.

Required Qualifications:

• - 7+ years of experience in enterprise software/platform engineering.
• - Proven expertise in GenAI technologies (LLMs, transformers, vector DBs, etc.).
• - Strong experience with cloud infrastructure and GPU resource optimization.
• - Proficiency in Python and ML/LLM tooling (e.g., LangChain, HuggingFace, PyTorch).
• - Deep understanding of MLOps, model evaluation, and compliance in AI.
• - Experience building developer tooling and reusable code frameworks.
• - Excellent communication skills and ability to work in highly collaborative environments.

Preferred Qualifications:

• - Experience in regulated industries (finance, healthcare, etc.).
• - Familiarity with enterprise security and compliance controls for AI.
• - Previous consulting or client-facing engineering experience.

Engagement Model:

• Hands-on coding, strategic design, and direct collaboration with internal teams.
  Knowledge transfer as a key engagement objective.
  On-site presence for collaborative development.
  Iterative delivery of working prototypes and production-ready components.

Success Metrics:

• - Delivery of functional, scalable GenAI platform components.
• - Reduction in development time through reusable assets.
• - Independent implementation success by company teams.
• - Measurable improvements in productivity and infrastructure utilization.

This role may require on-location work with WWT customers. Some customers may require WWT employees and contractors coming on-site to be vaccinated against COVID-19 and/or to receive frequent negative COVID-19 testing.

Equal Opportunity Employer Minorities/Women/Veterans/Differently Abled