GenAI Engineer_Alpharetta, GA_Locals

GenAI Engineer(s) -
*Location:* Hybrid – Alpharetta, GA Need local only
*Openings:* Multiple positions across experience levels
### Role Overview
Need experienced *GenAI Engineers* to support AT&T. You will design, build, and deploy enterprise-grade Generative AI solutions that integrate large language models (LLMs), RAG, and intelligent agents into production systems at scale.
This is an end-to-end engineering role spanning architecture, development, deployment, and optimization. You will partner with engineering, product, and business teams to deliver reliable GenAI solutions that drive measurable business outcomes.
### Key Responsibilities
* Design and develop end-to-end software solutions and architectures for enterprise production environments.
* Build scalable backend services and APIs using *Python, FastAPI, Flask, or Django* and SQL/NoSQL databases.
* Develop and optimize prompts across *OpenAI, Anthropic, and open-source LLMs*.
* Implement context engineering strategies, including *session management, vector search, knowledge retrieval, and RAG*.
* Build and integrate *AI agents and agentic workflows* into enterprise applications.
* Develop conversational and multi-agent workflows using frameworks such as *LangGraph*.
* Design distributed systems for enterprise-scale *performance, reliability, and scalability*.
* Containerize applications using *Docker* and support CI/CD deployment on cloud infrastructure.
* Collaborate with cross-functional engineering and product teams to solve complex technical problems.
### Must-Have Qualifications
* Strong experience in *end-to-end software engineering and system architecture*.
* Proven experience building and deploying *enterprise production systems*.
* Extensive *Java and/or Python* architecture and development experience.
* Strong full-stack Python experience, including *FastAPI, Flask, Django, SQL, and NoSQL*.
* Hands-on expertise with *LLMs and prompt engineering*.
* Strong understanding of *context engineering, RAG, vector search, session management, and knowledge retrieval*.
* Production experience integrating *AI agents and LLMs* into applications.
* Experience with *LangGraph or comparable agent/workflow frameworks*.
* Familiarity with *cloud infrastructure, Docker, and CI/CD*.
* Experience designing *distributed and scalable enterprise systems*.
* Strong analytical, problem-solving, and communication skills.
### Preferred
* Contributions to *open-source LLM, AI agent, RAG, or prompt-engineering projects*.
* Experience deploying GenAI applications at enterprise scale.
* Experience evaluating and optimizing LLM applications for *quality, latency, reliability, and cost*.