Data Scientist / AI Architect (Agentic AI & LLM Focus)

Role:

Data Scientist / AI Architect (Agentic

AI & LLM

Focus)

Location:

2-3 days / week in the client s Irvine office, 1 day in their downtown LA office, 1 day remote

Onsite:

Yes Rate:

$90/Hr On C2C We are engaging a hands-on Data Scientist / AI Architect to design and deliver agent-based, AI-enabled workflows integrated with enterprise systems. The role requires close collaboration with internal teams and business stakeholders to translate use cases into scalable, production-grade solutions. Core Responsibilities Data Science & Agent-Oriented System Design Design, develop, and deploy Python-based data science solutions supporting: o Agent-driven workflows (supervisor/sub-agent architectures, intelligent decision systems) o Data pipelines, APIs, and enterprise system integrations for model deployment o Multi-step, asynchronous processing and experimentation workflows Apply strong data science and engineering practices, including: o Model validation and evaluation o Testing and reproducibility o Code quality, performance optimization, and error handling AI / LLM-Enabled Solution Development Design and implement end-to-end LLM-powered solutions, including: o Prompt engineering and context management to optimize model performance o Structured output generation, validation, and post-processing for reliable outcomes Integrate LLMs into analytical pipelines and decision-making workflows Stakeholder Collaboration Work closely with business stakeholders to: o Translate business use cases into technical designs and acceptance criteria o Communicate trade-offs across quality, cost, risk, and delivery timelines Good to Have Data Engineering for Retrieval-Based Systems Design and manage retrieval pipelines to support grounding and context enrichment, including: o Vector databases and similarity search o Search and indexing systems o Storage solutions for source data and embeddings o Caching strategies for performance and scalability Cloud-Native Delivery (AWS Preferred) Deploy and manage AI/ML solutions on cloud platforms, with focus on: o IAM and security best practices o Scalability, resilience, and availability o CI/CD pipelines and environment management Integration & UX Enablement Integrate AI solutions with enterprise tools via secure APIs and gateways Collaborate with front-end teams (e.g., React) to enable seamless user experiences Observability & Operations Implement monitoring across workflows, including: o Logging, metrics, and tracing for agent pipelines and model calls Support performance tuning, incident diagnosis, and continuous optimization Screening / Interview Focus Areas Hands-on experience in AI/LLM solution design and implementation Strong understanding of

AI/ML/LLM

libraries used in projects Experience with LLM fine-tuning (critical requirement) Experience in RAG (Retrieval-Augmented Generation) architectures