Principal AI Solutions Architect

Title: Principal AI Solutions Architect

Location: Concord, CA

Duration: 6 months

Work Engagement: W2

Compensation: $120-128/hr is the pay range that the employer reasonably expects to pay for this position

Work Schedule: Hybrid 3 days in office/2 days remote

Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits

Summary:

In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Specialty Software Engineering. Review and analyze complex multi-faceted, larger scale, or longer-term Specialty Software Engineering challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel. Required Qualifications: Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.

Key Requirements:

• Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.

Core Technical Skills

• Python software engineering
• REST API development
• Microservices architecture
• Distributed systems design
• Backend service development
• FastAPI
• AsyncIO
• Multiprocessing
• Performance tuning and profiling
• Caching strategies
• Database/query optimization
• Event-driven architecture
• High-availability and fault-tolerant system design

Generative AI / LLM Skills

• Generative AI application development
• Large Language Models
• Agentic AI systems
• Multi-agent workflow design
• Retrieval-Augmented Generation
• Hybrid RAG architectures
• Knowledge graph-enhanced RAG
• Prompt engineering
• Prompt orchestration
• Tool calling
• LLM routing and fallback strategies
• Fine-tuning evaluation
• Model evaluation frameworks
• Hallucination detection
• Human-in-the-loop validation
• Text-to-SQL using LLMs
• Schema-aware prompting
• Embeddings and semantic search

AI Platform & Architecture Skills

• Enterprise AI platform architecture
• Scalable AI workflow design
• AI governance standards
• AI guardrails implementation
• Responsible AI controls
• PII redaction
• Audit logging
• Model usage monitoring
• Latency, cost, and accuracy optimization
• AI/ML feature engineering
• Recommendation systems
• Feedback loops for model improvement