Onsite_Backend Engineer – Agentic AI & LLM Systems in AZ

Title: Senior Backend Engineer – Agentic AI & LLM Systems

Location: Phoenix, AZ (Onsite)

Work Arrangement: Onsite

Employment Type: Contract

Duration: 6 Months

Primary Skills: Agentic AI, LLM, Rest API

Job Summary

We are seeking an experienced Senior Backend Engineer specializing in Agentic AI and Large Language Model (LLM) systems to design, develop, and maintain scalable, high-performance backend services and production-grade autonomous AI systems. The ideal candidate will have strong expertise in Node.js, TypeScript and/or Go, distributed systems, cloud infrastructure, and agentic AI workflows.

The role involves owning shared agentic AI capabilities across multiple products, driving architectural decisions, and delivering reliable, secure, and cost-effective autonomous systems. The candidate will collaborate with cross-functional teams to establish technical direction, improve system performance, and translate complex business requirements into scalable engineering solutions.

Key Responsibilities

Design, develop, and maintain high-performance backend services, REST APIs, and microservices for scalable applications.

Architect, build, and operate production-grade agentic AI systems and shared capabilities used across multiple products and teams.

Drive technical direction for agentic AI initiatives, defining architecture patterns, autonomy boundaries, and system design principles.

Design and implement agent frameworks, orchestration layers, planning mechanisms, tool integration, memory management, and evaluation strategies.

Develop Retrieval-Augmented Generation (RAG) pipelines to improve information retrieval, contextual grounding, and response quality.

Build and optimize LLM infrastructure, model gateways, inference pipelines, and related AI platform capabilities.

Implement observability, evaluation, monitoring, and safety mechanisms to ensure the reliability and responsible operation of autonomous AI systems.

Design and optimize distributed, event-driven architectures using technologies such as Apache Kafka, asynchronous processing, queues, and streaming systems.

Optimize backend systems for performance, scalability, reliability, availability, and cost efficiency under high workloads.

Lead technical design reviews and guide engineering teams through architectural trade-offs involving autonomy, safety, scalability, reliability, and cost.

Collaborate with DevOps and platform teams to deploy, manage, and monitor services in cloud environments such as AWS and Google Cloud Platform (GCP).