Looking for Data Scientist / AI Architect (Agentic AI & LLM Focus) @Irvine/Downtown LA, CA Onsite (Locals Preferred)

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Hi,

Hope you are doing well!

We have an urgent requirement for an Data Scientist / AI Architect (Agentic AI & LLM Focus) @Irvine/Downtown LA, CA Onsite with our Client. Please review the details below and let me know if you are interested.

Job Title: Data Scientist / AI Architect (Agentic AI & LLM Focus)

Work Location: Irvine/Downtown LA, CA Onsite

Context & Objective

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: • Agent-driven workflows (supervisor/sub-agent architectures, intelligent decision systems) • Data pipelines, APIs, and enterprise system integrations for model deployment • Multi-step, asynchronous processing and experimentation workflows • Apply strong data science and engineering practices, including: • Model validation and evaluation • Testing and reproducibility • Code quality, performance optimization, and error handling

AI / LLM-Enabled Solution Development

• Design and implement end-to-end LLM-powered solutions, including: • Prompt engineering and context management to optimize model performance • 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: • Translate business use cases into technical designs and acceptance criteria • 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: • Vector databases and similarity search • Search and indexing systems • Storage solutions for source data and embeddings • Caching strategies for performance and scalability

Cloud-Native Delivery (AWS Preferred)

• Deploy and manage AI/ML solutions on cloud platforms, with focus on: • IAM and security best practices • Scalability, resilience, and availability • 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: • 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

Thanks and Regards,

Akshitha Gunukula || US IT Recruiter

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