Full Stack Engineer

Job Description

AI Full Stack Engineer

Status: Must be legally eligible to work where you live.

Resume must be in English

Location : Remote - some travel to Atlanta, GA

Engagement : Contract, Long Term, Full Time

About the Role

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.

This is a high-impact, individual-contributor role for someone who is passionate about autonomous AI systems and has the scars to prove it.

Key Responsibilities

\n
• Design and develop AI agents — including autonomous, multi-step, and tool-using agents — using AWS Bedrock and leading agentic frameworks.
\n
• Build, fine-tune, and integrate Large Language Models (LLMs) and Small Language Models (SLMs) into production workflows.
\n
• Develop backend services and agent orchestration layers using Node.js and Python .
\n
• Implement agent monitoring, observability, and evaluation pipelines using tools such as Fiddler AI and comparable platforms.
\n
• Collaborate with product and engineering teams to translate business requirements into robust AI-powered features.
\n
• Establish best practices for responsible AI , prompt engineering, model evaluation, and agent safety.
\n
• Continuously evaluate emerging models, frameworks, and tooling to keep the platform at the cutting edge.
\n
• Contribute to internal documentation, architecture reviews, and knowledge sharing across the team.
\n

Required Qualifications

3+ years of professional software engineering experience , including hands-on experience building AI/LLM-powered applications.

Cloud & Infrastructure

\n
• AWS Bedrock — hands-on experience building and deploying models and agents on the Bedrock platform (foundation model access, Knowledge Bases, Agents for Bedrock).
\n
• Familiarity with broader AWS ecosystem (Lambda, S3, IAM, API Gateway, etc.).
\n

Agent Development

\n
• Proven, hands-on experience building AI agents — including autonomous agents , tool-calling agents, ReAct / plan-and-execute patterns, and multi-agent orchestration.
\n
• Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or AWS Bedrock Agents.
\n
• Strong understanding of agent memory, context management, and tool use .
\n

Languages & Frameworks

\n
• Python — proficient; used for ML pipelines, agent logic, data processing, and scripting.
\n
• Node.js — proficient; used for API development, backend services, and agent integration layers.
\n

LLM / SLM Expertise

\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).
\n
• Practical knowledge of prompt engineering , few-shot learning, RAG (Retrieval-Augmented Generation), and fine-tuning workflows.
\n

Monitoring & Observability

\n
• Experience with Fiddler AI or comparable agent/model monitoring tools (e.g., LangSmith, Arize, Weights & Biases, Helicone).
\n
• Ability to define and track agent performance metrics: accuracy, latency, hallucination rate, tool-call success, and cost.
\n

Preferred Qualifications

\n
• Experience with vector databases (Pinecone, pgvector, OpenSearch, Weaviate) for semantic search and RAG pipelines.
\n
• Familiarity with MLOps practices — CI/CD for models, model versioning, A/B evaluation.
\n
• Exposure to multi-modal models (vision + language).
\n
• Prior work in an AI product or platform team at scale.
\n
• AWS certifications (e.g., AWS Certified Machine Learning — Specialty) are a plus.
\n

What We're Looking For

\n
• Hands-on builder — You write code, ship agents, and debug production issues — not just architect on whiteboards.
\n
• Curiosity-driven — You stay current with the fast-moving AI landscape and bring new ideas to the team.
\n
• Ownership mindset — You take a feature from idea to production and care about it long after launch.
\n
• Clear communicator — You can explain complex AI behavior to non-technical stakeholders without dumbing it down.
\n

Why Join Us

\n
• Work on cutting-edge agentic AI systems that are deployed at enterprise scale.
\n
• 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.
\n
• Collaborative, low-ego culture with a strong bias for shipping.
\n
• Competitive compensation, flexible work arrangements, and continuous learning support.
\n