Role: AI Architect/AI Software Engineer-Python Backend
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 & Objective
We 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.
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Backend & Agent-Oriented Engineering
Build and maintain Python-based backend services supporting:
o Agent orchestration (supervisor/sub-agent patterns)
o APIs and system integrations
o 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 management
o Structured outputs and validation
Data Engineering for Retrieval-Based Systems
Design and operate retrieval pipelines to support grounding and context enrichment, including:
o Vector search and similarity retrieval
o Search and indexing solutions
o Object storage for source content and embeddings
o Caching for performance and scalability
Cloud-Native Delivery
Deploy and operate services primarily on AWS, following best practices for:
o IAM and security
o Scalability, resiliency, and availability
o 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 criteria
o Communicate trade-offs across quality, cost, risk, and delivery timelines
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