Ai Full Stack Architect Only Usc

Ai Full Stack Architect Only (USC & GC)

12 months contract
Atlanta, GA (Hybrid)

About the Role

We are seeking an AI Full Stack Architect to join our AI Center of Excellence. This is a senior individual-contributor and technical leadership role for someone who has spent years in the trenches - building, shipping, and scaling AI-powered systems - and is now ready to set the architectural direction for the next generation of intelligent applications.

You will own the end-to-end design and delivery of agentic AI systems, LLM-powered platforms, and full stack applications that operate at enterprise scale. You bring deep hands-on expertise across AWS Bedrock, Python, Node.js, and modern front-end frameworks, and you know how to translate that into production-grade architecture that others can build on.

Level & Scope

Key Responsibilities

Agent Architecture & Development

Architect and build autonomous, multi-step, and tool-using AI agents using AWS Bedrock Agents and leading agentic frameworks.

Design multi-agent orchestration topologies - including supervisor/worker patterns, parallel execution, and handoff protocols.

Establish agent design patterns: memory management, context windows, tool-call sequencing, retry logic, and failure recovery.

Define guardrails, safety layers, and responsible AI standards for all agent-based systems.

LLM / SLM Integration

Own the selection, integration, and lifecycle management of Large Language Models (Claude, GPT-4, Llama, Mistral) and Small Language Models (Phi-3, Gemma, Mistral 7B).

Design and implement RAG pipelines, prompt engineering standards, few-shot frameworks, and fine-tuning workflows.

Establish model benchmarking and evaluation criteria - balancing capability, latency, cost, and safety.

Cloud & Infrastructure (AWS)

Lead the design of AI infrastructure on AWS Bedrock - including foundation model access, Knowledge Bases, and Bedrock Agents.

Architect cloud-native backend services using Lambda, API Gateway, ECS/EKS, S3, and IAM.

Define infrastructure-as-code standards and CI/CD pipelines for AI workloads.

Full Stack Development

Build and architect full stack applications - React/Next.js front ends, Node.js backend services, and Python agent/ML pipelines.

Design streaming agent UIs, chat interfaces, and real-time AI-powered user experiences.

Own API design and integration patterns between front-end, backend, and AI layers.

Monitoring, Observability & Evaluation

Implement agent monitoring and evaluation pipelines using Fiddler AI and comparable platforms (LangSmith, Arize, Weights & Biases, Helicone).

Define and track agent performance metrics: accuracy, latency, hallucination rate, tool-call success rate, and cost-per-interaction.

Build feedback loops that drive continuous model and agent improvement.

Technical Leadership

Lead architecture reviews, design documents, and RFC processes for AI initiatives.

Mentor and upskill engineers on agent development, LLM integration, and AI best practices.

Partner with product, data, and platform teams to translate business requirements into scalable AI solutions.

Continuously evaluate emerging models, frameworks, and tooling - bringing the best to the team.

Required Qualifications

AWS & Cloud

AWS Bedrock - deep, hands-on experience building and deploying agents and models (Bedrock Agents, Knowledge Bases, foundation model APIs).

Strong working knowledge of the broader AWS ecosystem: Lambda, S3, IAM, API Gateway, ECS/EKS, CloudWatch.

Experience designing cloud-native, serverless, and containerized AI workloads.

Agent Development

Proven, hands-on experience building autonomous agents, tool-calling agents, ReAct / plan-and-execute patterns, and multi-agent systems.

Deep experience with agentic frameworks: LangChain, LangGraph, AutoGen, CrewAI, or AWS Bedrock Agents.

Strong command of agent memory, context management, tool use, and orchestration design.

Languages & Frameworks

Python - expert-level; ML pipelines, agent logic, data processing, API services.

Node.js - expert-level; backend services, API development, agent integration layers.

Front-end - proficient in React or Next.js; able to build and architect AI-powered UIs including streaming chat and agent interfaces.

LLM / SLM Expertise

Hands-on production experience with LLMs (Claude, GPT-4, Llama, Mistral) and SLMs (Phi-3, Gemma, Mistral 7B).

Deep practical knowledge of prompt engineering, RAG, few-shot learning, and fine-tuning workflows.

Experience owning model evaluation, selection, and cost/capability trade-off decisions.

Monitoring & Observability

Hands-on experience with Fiddler AI or comparable monitoring platforms (LangSmith, Arize, W&B, Helicone).

Ability to define, instrument, and track agent and model performance metrics end-to-end.

Preferred Qualifications

Experience with vector databases (Pinecone, pgvector, OpenSearch, Weaviate) for semantic search and RAG pipelines.

Familiarity with MLOps practices - CI/CD for models, model versioning, A/B evaluation, drift detection.

Exposure to multi-modal models (vision + language).

Prior experience in an AI product or platform team at scale, in a full stack or architect capacity.

AWS certifications - AWS Certified Solutions Architect (Professional) or AWS Certified Machine Learning - Specialty.