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*.
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