Job Description & Details
The GenAI wave is reshaping how enterprises automate their infrastructure, making expertise in AI‑augmented DevOps hotter than ever. Companies are racing to embed large‑language models into their pipelines, and a Systems Engineer with a GenAI focus sits at the center of that transformation. This role offers a chance to lead AI‑driven workflow innovation while working on‑site in Alpharetta’s growing tech hub.
Job Summary
We are looking for a senior‑level Systems Engineer to design, build, and maintain AI‑powered microservices that streamline DevOps and infrastructure workflows. The role blends Java backend development, prompt engineering for LLMs, and end‑to‑end cloud automation using Docker, Kubernetes, and CI/CD pipelines. You will collaborate with architects, QA, and product leads to deliver secure, ethical, and high‑quality AI solutions on an on‑site basis.
Top 3 Critical Skills Table
| Skill | Why it's critical | Mastery Level |
|---|---|---|
| Prompt & Agentic AI Engineering | Drives the core value of GenAI‑enhanced workflows and LLM reliability | Senior |
| Cloud & DevOps (Docker, Kubernetes, CI/CD) | Enables scalable, repeatable deployment of AI services across environments | Senior |
| Java & Python Backend Development | Powers the microservice architecture and integrates with RESTful APIs | Senior |
Interview Preparation
- How do you design prompts to improve LLM output consistency?
What the interviewer is looking for: Understanding of prompt engineering techniques, evaluation metrics, and iterative testing. - Explain how you would containerize a Java‑based microservice and deploy it on Kubernetes.
What the interviewer is looking for: Knowledge of Dockerfile best practices, Helm charts, health checks, and scaling strategies. - Describe a CI/CD pipeline you built for an AI‑centric application. Which tools did you use and why?
What the interviewer is looking for: Experience with tools like GitHub Actions, Jenkins, or Azure DevOps, and how they handle model artifacts and testing. - What are the security considerations when exposing GenAI models via REST APIs?
What the interviewer is looking for: Awareness of authentication, rate limiting, data sanitization, and ethical AI safeguards. - Can you walk us through an implementation of an Agentic Framework such as LangChain?
What the interviewer is looking for: Practical experience with chaining LLM calls, memory management, and tool integration.
Resume Optimization
- GenAI
- Large Language Models (LLM)
- Prompt Engineering
- Agentic AI / LangChain
- Cloud (AWS/Azure/GCP)
- DevOps & CI/CD
- Docker & Kubernetes
- Java backend development
- Python programming
- RESTful APIs
Application Strategy
When you email the recruiter, start with a courteous greeting and attach your updated resume. Clearly highlight your top three relevant skills—such as Prompt Engineering, Cloud/DevOps automation, and Java backend development—and reference specific projects where you applied them. Mention any experience with Agentic frameworks like LangChain and emphasize your ability to deliver secure, production‑grade AI services.
Career Roadmap
| Current Role | Typical Experience | Core Focus | Next Position |
|---|---|---|---|
| Systems Engineer – GenAI | 8‑12 yrs, AI‑enabled DevOps | AI workflow automation, microservice design | Senior Systems Engineer – GenAI |
| Senior Systems Engineer – GenAI | 12‑15 yrs, end‑to‑end platform ownership | Scaling AI platforms, team mentorship | Lead AI Platform Engineer |
| Lead AI Platform Engineer | 15+ yrs, cross‑functional leadership | Strategy, architecture, multi‑team delivery | Director of AI Engineering |