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:$85-90/Hr On C2C   Must Have Skills• Skill 1 - Python backend development• Skill 2 - Agent-based / agent-oriented workflow development• Skill 3 - API development and system integration• Skill 4 - LLM-enabled application development (prompt & context management, structured outputs)• Skill 5 - Retrieval-based systems (vector search, indexing, embeddings)• Skill 6 - AWS cloud-native development• Skill 7 - CI/CD and environment management• Skill 8 - Observability (logging, metrics, tracing)       Context & ObjectiveWe are engaging a software engineer to support the design and delivery of agent-based, AI-enabled workflows that integrate with enterprise systems. The contractor will work closely with internal teams and business stakeholders to translate use cases into robust, scalable solutions.________________________________________Backend & Agent-Oriented Engineering• Build and maintain Python-based backend services supporting:o Agent orchestration (supervisor/sub-agent patterns)o APIs and system integrationso Multi-step, asynchronous workflows• Apply strong engineering practices (testing, code quality, error handling).AI / LLM-Enabled Application Development• Deliver LLM-enabled features end to end, including:o Prompt and context managemento Structured outputs and validationData Engineering for Retrieval-Based Systems• Design and operate retrieval pipelines to support grounding and context enrichment, including:o Vector search and similarity retrievalo Search and indexing solutionso Object storage for source content and embeddingso Caching for performance and scalability Cloud-Native Delivery• Deploy and operate services primarily on AWS, following best practices for:o IAM and securityo Scalability, resiliency, and availabilityo CI/CD and environment management Integration & UX Enablement• Integrate with enterprise tools and services via secure APIs and gateways.• Support React-based front-end patterns and collaboration integrations to enable effective user experiences.Observability & Operations• Implement logging, metrics, and tracing across agent workflows, model calls, and integrations.• Support incident diagnosis, performance tuning, and ongoing optimisation.Working with the Business• Engage directly with business stakeholders to:o Translate use cases into technical designs and acceptance criteriao Communicate trade-offs across quality, cost, risk, and delivery timelines