Kforce Technology Staffing
Responsibilities
Solution Architecture: Design and implement scalable GenAI solutions across AWS and Azure environments, ensuring security, compliance, and performance
Cloud Integration: Architect multi-cloud platforms leveraging AWS Bedrock, Azure OpenAI, and related services for LLM-based applications
Infrastructure as Code: Implement automation using Terraform, CloudFormation, or Azure Resource Manager templates
Model Lifecycle Management: Fine-tune, optimize, and deploy models using AWS SageMaker, Azure Machine Learning, and integrate with enterprise APIs
Security & Compliance: Apply best practices for data protection, responsible AI, and regulatory compliance (GDPR, CCPA, HIPAA)
Technical Leadership: Mentor engineering teams on GenAI, MLOps/LLMOps, and agentic AI system design
Requirements
Master’s degree in Computer Science, Engineering, or related field is preferred
Certifications: AWS Certified Solutions Architect, Azure Solutions Architect Expert, or AI/ML specialty certifications (preferred)
Soft Skills: Strong communication, stakeholder management, and ability to translate business needs into technical solutions
Cloud Expertise
AWS: Bedrock, SageMaker, Lambda, ECS/EKS, S3
Azure: Azure OpenAI, Azure ML, Cognitive Services, AKS
Programming: Python (TensorFlow, PyTorch, HuggingFace), plus Java/.NET for backend microservices
GenAI Tools: AWS Bedrock, OpenAI APIs (GPT, DALL.E, Whisper), LangChain, RAG pipelines
DevOps/MLOps: Docker, Kubernetes, CI/CD pipelines, observability tools
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce’s sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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Solution Architecture: Design and implement scalable GenAI solutions across AWS and Azure environments, ensuring security, compliance, and performance
Cloud Integration: Architect multi-cloud platforms leveraging AWS Bedrock, Azure OpenAI, and related services for LLM-based applications
Infrastructure as Code: Implement automation using Terraform, CloudFormation, or Azure Resource Manager templates
Model Lifecycle Management: Fine-tune, optimize, and deploy models using AWS SageMaker, Azure Machine Learning, and integrate with enterprise APIs
Security & Compliance: Apply best practices for data protection, responsible AI, and regulatory compliance (GDPR, CCPA, HIPAA)
Technical Leadership: Mentor engineering teams on GenAI, MLOps/LLMOps, and agentic AI system design
Requirements
Master’s degree in Computer Science, Engineering, or related field is preferred
Certifications: AWS Certified Solutions Architect, Azure Solutions Architect Expert, or AI/ML specialty certifications (preferred)
Soft Skills: Strong communication, stakeholder management, and ability to translate business needs into technical solutions
Cloud Expertise
AWS: Bedrock, SageMaker, Lambda, ECS/EKS, S3
Azure: Azure OpenAI, Azure ML, Cognitive Services, AKS
Programming: Python (TensorFlow, PyTorch, HuggingFace), plus Java/.NET for backend microservices
GenAI Tools: AWS Bedrock, OpenAI APIs (GPT, DALL.E, Whisper), LangChain, RAG pipelines
DevOps/MLOps: Docker, Kubernetes, CI/CD pipelines, observability tools
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce’s sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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