AI Full Stack Engineer
Long term Contract
Atlanta, GA - Hybrid
This is a high-impact, individual-contributor role for someone who is equally comfortable building a React UI, designing a Python agent pipeline, and deploying it all on AWS and has the scars to prove it.
Key Responsibilities
Design and develop AI agents including autonomous, multi-step, and tool-using agents using AWS Bedrock and leading agentic frameworks.
Build, fine-tune, and integrate Large Language Models (LLMs) and Small Language Models (SLMs) into production workflows.
Develop full stack applications from responsive front-end UIs to backend services and agent orchestration layers using Node.js, Python, and modern front-end frameworks.
Implement agent monitoring, observability, and evaluation pipelines using tools such as Fiddler AI and comparable platforms.
Collaborate with product and engineering teams to translate business requirements into robust AI-powered features.
Establish best practices for responsible AI, prompt engineering, model evaluation, and agent safety.
Continuously evaluate emerging models, frameworks, and tooling to keep the platform at the cutting edge.
Contribute to internal documentation, architecture reviews, and knowledge sharing across the team.
Required Qualifications
Cloud & Infrastructure
AWS Bedrock hands-on experience building and deploying models and agents on the Bedrock platform (foundation model access, Knowledge Bases, Agents for Bedrock).
Familiarity with broader AWS ecosystem (Lambda, S3, IAM, API Gateway, etc.).
Agent Development
Proven, hands-on experience building AI agents including autonomous agents, tool-calling agents, ReAct / plan-and-execute patterns, and multi-agent orchestration.
Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or AWS Bedrock Agents.
Strong understanding of agent memory, context management, and tool use.
Languages & Frameworks
Python proficient; used for ML pipelines, agent logic, data processing, and scripting.
Node.js proficient; used for API development, backend services, and agent integration layers.
Front-end working knowledge of a modern front-end framework (React, Next.js, or Vue) to build AI-powered user interfaces and chat/agent experiences.
LLM / SLM Expertise
Hands-on experience working with Large Language Models (e.g., Claude, GPT-4, Llama, Mistral) and Small Language Models (e.g., Phi-3, Gemma, Mistral 7B).
Practical knowledge of prompt engineering, few-shot learning, RAG (Retrieval-Augmented Generation), and fine-tuning workflows.
Monitoring & Observability
Experience with Fiddler AI or comparable agent/model monitoring tools (e.g., LangSmith, Arize, Weights & Biases, Helicone).
Ability to define and track agent performance metrics: accuracy, latency, hallucination rate, tool-call success, and cost.
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.
Exposure to multi-modal models (vision + language).
Prior work in an AI product or platform team at scale, ideally in a full stack capacity.
Experience integrating AI capabilities (streaming responses, tool calls, agent UIs) into front-end applications.
AWS certifications (e.g., AWS Certified Machine Learning Specialty) are a plus.
What We're Looking For
Trait
What it means here
Hands-on builder
You write code, ship agents, and debug production issues not just architect on whiteboards.
Curiosity-driven
You stay current with the fast-moving AI landscape and bring new ideas to the team.
Ownership mindset
You take a feature from idea to production and care about it long after launch.
Clear communicator
You can explain complex AI behavior to non-technical stakeholders without dumbing it down.
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