.Net Developer with AWS

Saxon Global•Atlanta, GA

19h

About The Position

We're looking for a strong Software Engineer with hands-on AWS experience who can contribute across both traditional application development and emerging AI capabilities. Early work will be POC-heavy around chatbots and LLM-based features, but you'll also be doing real, day-to-day development work. We need someone versatile who can move between both worlds without getting siloed.

Requirements

Strong .NET or Python development background — required
Hands-on AWS experience with Bedrock
5+ years in software engineering with solid experience building and shipping production applications
Experience or strong familiarity with LLMs, chatbot frameworks, and agentic AI patterns
Comfortable with Python alongside .NET for AI/ML-related work
Solid skills in API design, secure integrations, automated testing, and CI/CD pipelines
Experience with or exposure to RAG pipelines — embeddings, vector databases (FAISS, Pinecone, OpenSearch), and retrieval tuning
Able to context-switch between standard feature development and AI prototyping without losing momentum
Good communicator — can explain technical trade-offs in plain language to both engineers and business stakeholders
Comfortable working in Agile with cross-functional teams
BA/BS required (CS, CIS, MIS, or related)

Responsibilities

Build and maintain applications in .NET within an AWS environment
Develop proof-of-concepts around chatbot, agentic AI, and LLM use cases, then iterate toward production-ready features
Create LLM-based objects and integrations using AWS Bedrock and its available tooling (agents, knowledge bases, model invocation)
Design and build tools and features that support chatbot functionality — conversation flows, tool/function calling, and integration with existing enterprise systems
Write production-quality code — clean APIs, automated testing, CI/CD pipelines, and maintainable architecture
Collaborate across teams — work with business stakeholders to understand what's realistic with GenAI, and with engineering teams to deliver it
Prototype fast, then harden — move from quick experiments to reliable, deployed features
Help establish patterns for prompt engineering, orchestration, and evaluation as AI capabilities mature across the team
Work with business teams to understand what they need from GenAI, help figure out what's realistic, and map out how to build it.
Build and own chatbot and agentic AI solution
Evaluate and select the right models for the job based on latency, cost, data privacy needs, and output quality. Stay current on what's available across providers.
Set up and maintain LLMOps workflows — deployment pipelines, monitoring, prompt versioning, evaluation frameworks, incident response, and cost tracking across environments.
Work with security, privacy, and compliance teams to make sure everything meets enterprise standards (HIPAA, GDPR, internal policies, etc.).
Help level up other engineers through pairing, code reviews, and design sessions.
Set clear patterns for prompt engineering, orchestration frameworks (LangChain, Semantic Kernel, etc.), and evaluation-driven development.
Write and maintain engineering standards for GenAI work — coding standards, prompt/policy guidelines, evaluation gates, and release checklists.
Communicate technical decisions and trade-offs clearly to both engineers and non-technical stakeholders.