Remote Senior Generative AI Engineer

Hired; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Hired, a leading tech staffing platform, is seeking a Senior LLM Engineer for a fully remote, full-time role. You will design, build, and deploy generative AI solutions using Python and modern LLM frameworks.

Collaborate with cross-functional teams to shape the technical roadmap, implement RAG pipelines and prompt engineering, and translate business needs into scalable AI systems.

Engage in code reviews, tuning, embeddings work, and performance optimization across cloud platforms.

Qualifications

• Proficient in Python and SQL for AI system development.
• Experience with LangChain and modern LLM frameworks.
• Deep understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows.
• Background in machine learning or software engineering with system-level thinking.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Ability to work independently while collaborating effectively across teams.
• Excellent communication and stakeholder management skills.

Responsibilities

• Design and develop generative AI and LLM-based systems using LangChain and RAG pipelines.
• Implement prompt engineering techniques and agent-based frameworks.
• Collaborate with the engineering team to shape the technical roadmap for LLM initiatives.
• Translate business needs into scalable, production-ready AI solutions.
• Contribute to architecture discussions, code reviews, and performance optimization.

Skills

Python

SQL

LLM concepts

Prompt engineering

Agent workflows

Cross-functional collaboration

Education

Bachelor's degree in CS or related field

Tools

LangChain

Retrieval-Augmented Generation

Embeddings

Vector databases

Cloud platforms (AWS/Azure/GCP)

Job description

Hired, a leading tech staffing platform, is seeking a Senior LLM Engineer for a fully remote, full-time role. You will design, build, and deploy generative AI solutions using Python and modern LLM frameworks.

Collaborate with cross-functional teams to shape the technical roadmap, implement RAG pipelines and prompt engineering, and translate business needs into scalable AI systems.

Engage in code reviews, tuning, embeddings work, and performance optimization across cloud platforms.