Technology

Gen AI Engineer--Need Locals or Near-by--F2F

KeylentAlpharetta, GA🇺🇸United States

Why this role stands out

This hybrid role offers an exciting opportunity to design and deploy cutting-edge Generative AI solutions, integrating LLMs and intelligent agents into production systems. You'll thrive here if you're a mid-senior level engineer passionate about end-to-end AI development and eager to contribute to enterprise-grade projects. Apply now to shape the future of AI with Keylent!

Quick overview

SeniorityMid Senior

Work modeHybrid

LocationAlpharetta, GA, United States

DjangoDockerFastAPIFlaskSQLJavaLLMPython

Job description

Hi All,

Good Morning,

We have an urgent position for the below mentioned requirement.

Title: GenAI Engineer(s)

Location: Hybrid – Alpharetta, GA Need local only

Openings: Multiple positions across experience levels.

Note: Need only locals—F2F Mandate

Role Overview:

Need experienced *GenAI Engineers* 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*.