AI Application Engineer (LLMs & RAG)

Techventus; United States; Remote; USD 8,100 - 16,000; Full time

Benefits offered by this job

Remote-first work

AI projects exposure

Modern AI frameworks

Performance reviews

Job summary

Techventus is seeking an AI Application Engineer to build AI-powered applications, enterprise knowledge assistants, copilots, and RAG systems. You will connect language models to trusted business data and enterprise apps for real-world use.

Responsibilities include designing LLM-powered tools, building retrieval pipelines, and integrating AI with APIs and databases while ensuring security and scalable deployment. This role is remote with growth opportunities.

Qualifications

• Demonstrable AI application, RAG, or chatbot project.
• Ability to explain design decisions and evaluate model limitations.
• Strong analytical and problem-solving skills.
• Familiarity with cloud deployment and containerization is preferred.
• Experience with LangGraph, MCP, or agentic application patterns is an advantage.

Responsibilities

• Design and develop LLM-powered applications and AI assistants.
• Build RAG pipelines for documents, databases, and enterprise knowledge.
• Implement document ingestion, chunking, embeddings, retrieval, and reranking.
• Integrate LLMs with APIs, databases, and existing business applications.
• Implement structured outputs, tool calling, and multi-step AI workflows.
• Evaluate retrieval quality, response accuracy, latency, and cost.
• Apply access controls, data protection, and appropriate safeguards.
• Deploy, test, document, and maintain AI applications.

Skills

Python

LLM APIs

RAG pipelines

LangChain

LlamaIndex

SQL

REST APIs

Git

Testing

Security concepts

Education

Bachelor's degree in Computer Science or related field

Tools

LangGraph

MCP

Agentic patterns

Cloud deployment

Containerization

Job description

Techventus is looking for an AI Application Engineer to build AI-powered applications, enterprise knowledge assistants, copilots, retrieval-augmented generation (RAG) systems, and intelligent interfaces. The role involves connecting language models to trusted business information and engineering applications suitable for real-world use.

No. of Vacancies

1

Specific Skills

• Strong Python programming and software engineering fundamentals.
• Hands-on experience with LLM APIs and application development.
• RAG, embeddings, vector search, and retrieval evaluation.
• Familiarity with frameworks such as LangChain or LlamaIndex.
• SQL, REST APIs, Git, and automated testing.
• Understanding of authentication, data security, and deployment practices.

Responsible For

• Design and develop LLM-powered applications and AI assistants.
• Build RAG pipelines for documents, databases, and enterprise knowledge.
• Implement document ingestion, chunking, embeddings, retrieval, and reranking.
• Integrate LLMs with APIs, databases, and existing business applications.
• Implement structured outputs, tool calling, and multi-step AI workflows.
• Evaluate retrieval quality, response accuracy, latency, and cost.
• Apply access controls, data protection, and appropriate safeguards.
• Deploy, test, document, and maintain AI applications.

Additional Requirements

• Demonstrable AI application, RAG, or chatbot project.
• Ability to explain design decisions and evaluate model limitations.
• Strong analytical and problem-solving skills.
• Familiarity with cloud deployment and containerization is preferred.
• Experience with LangGraph, MCP, or agentic application patterns is an advantage.

Job Nature

Full Time

Educational Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
• Equivalent professional experience may be considered.

Experience Requirements

1 Year

Job Location

Full Remote

PKR 200,000–400,000 monthly, depending on technical depth and experience.

Other Benefits

• Remote-first work opportunities.
• Exposure to enterprise AI implementation projects.
• Opportunities to work with modern AI frameworks and deployment patterns.
• Professional development and performance reviews, subject to company policy.

Job Level

Sr. Position