Senior GenAI & LLM Engineer - Remote

Hire Feed; Pakistan; On-site; PKR 41,644,000 - 58,301,000; Full time

Job summary

Hire Feed is seeking a Senior LLM Engineer to design, build, and deploy generative AI solutions in a remote-fulltime role. You will work on LangChain-based systems, RAG pipelines, and prompt engineering while shaping the technical roadmap with cross-functional teams.

The role requires deep knowledge of LLM internals, embeddings, and vector databases, plus cloud experience (AWS/Azure/GCP) and strong communication skills for stakeholder alignment.

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 to deliver intelligent, context-aware solutions.
• 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

LangChain

LLM frameworks

Prompt engineering

Agent workflows

Communication

Cross-team collaboration

Tools

AWS

Azure

GCP

Vector databases

Embeddings

Job description

Hire Feed is seeking a Senior LLM Engineer to design, build, and deploy generative AI solutions in a remote-fulltime role. You will work on LangChain-based systems, RAG pipelines, and prompt engineering while shaping the technical roadmap with cross-functional teams.

The role requires deep knowledge of LLM internals, embeddings, and vector databases, plus cloud experience (AWS/Azure/GCP) and strong communication skills for stakeholder alignment.