Job Description
AI Full Stack Engineer
\n
\n
Status: Must be legally eligible to work where you live.
\n
Resume must be in English
\n
Location: Remote - some travel to Atlanta, GA
\n
Engagement: Contract, Long Term, Full Time
\n
\n
About the Role
\n
\n
We are looking for a hands-on AI Full Stack Engineer to join our growing AI Center of Excellence. In this role, you will design, build, and operationalize intelligent AI agents and LLM-powered solutions that drive real business impact. You will work at the intersection of cloud infrastructure, modern AI frameworks, and production-grade software engineering — owning the full lifecycle from prototype to deployment.
\n
This is a high-impact, individual-contributor role for someone who is passionate about autonomous AI systems and has the scars to prove it.
\n
\n
Key Responsibilities
\n
- \n
- 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 backend services and agent orchestration layers using Node.js and Python.
- 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.
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
Required Qualifications
\n
\n
3+ years of professional software engineering experience, including hands-on experience building AI/LLM-powered applications.
\n
\n
Cloud & Infrastructure
\n
- \n
- 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.).
\n
\n
\n
\n
Agent Development
\n
- \n
- 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.
\n
\n
\n
\n
\n
Languages & Frameworks
\n
- \n
- 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.
\n
\n
\n
\n
LLM / SLM Expertise
\n
- \n
- 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.
\n
\n
\n
\n
Monitoring & Observability
\n
- \n
- 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.
\n
\n
\n
\n
Preferred Qualifications
\n
- \n
- 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.
- AWS certifications (e.g., AWS Certified Machine Learning — Specialty) are a plus.
\n
\n
\n
\n
\n
\n
\n
What We're Looking For
\n
- \n
- 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.
\n
\n
\n
\n
\n
\n
Why Join Us
\n
- \n
- Work on cutting-edge agentic AI systems that are deployed at enterprise scale.
- Be part of the AI Center of Excellence — a team dedicated to pushing the boundaries of what AI can do inside and outside the organization.
- Collaborative, low-ego culture with a strong bias for shipping.
- Competitive compensation, flexible work arrangements, and continuous learning support.
\n
\n
\n
\n
\n