Principal AI Solutions Architect (contract)

Location: Concord, CA • Duration: 6 months • Work Engagement: W2

Pay

$120–128/hr

Schedule

Hybrid – 3 days in office, 2 days remote

Benefits

• Health Insurance
• Life Insurance
• 401K
• Voluntary Benefits

About the Role

In this contingent resource assignment, you will consult on complex initiatives with broad impact and large-scale planning for Specialty Software Engineering. You will review and analyze multi-faceted, larger-scale, or longer-term challenges requiring in-depth evaluation of multiple factors, including intangibles or unprecedented elements. You will contribute to resolving complex situations with a solid understanding of function, policies, procedures, and compliance requirements to meet deliverables. Strategically collaborate and consult with client personnel.

Requirements

• Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, consulting experience, training, military experience, or education.
• Applicants must be authorized to work for ANY employer in the U.S. (This position is not eligible for visa sponsorship.)

Skills

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