AI Engineer — Generative AI & Agentic Systems

Job Description

Cantor Dust is seeking a Junior AI Engineer with a strong interest in Generative AI, Agentic AI systems, and LLM-powered applications. You will work alongside senior engineers and domain experts to build automation workflows, retrieval systems, and production-ready AI solutions.

This role is ideal for someone with 1–2 years of experience who wants to deepen their expertise in modern AI systems while gaining exposure to deployment, client-facing solutions, and applied data engineering.

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## Key Responsibilities

### Generative AI & Agentic AI (Primary Focus)

·     ⁠Design and develop LLM-powered applications, assistants, copilots, and automation systems.

·     Build agentic workflows involving tool use, function calling, planning, orchestration, and structured outputs.

·     Develop Retrieval-Augmented Generation (RAG) systems using embeddings, vector databases, and enterprise knowledge sources.

·     Integrate commercial and open-source LLMs into internal tools and client-facing products.

·     Implement evaluation frameworks for quality, reliability, latency, and cost optimization.

·     Engineer prompts, workflows, and guardrails for production-grade AI systems.

·     ⁠Collaborate with senior engineers on AI architecture, experimentation, and deployment.

### Data & AI Infrastructure

·     ⁠Build and maintain data ingestion, transformation, and inference pipelines.

·     Work with structured and unstructured datasets from operational environments.

·     Support data quality, documentation, versioning, and reproducibility.

·     Develop metrics, reporting, and monitoring capabilities for AI applications.

### Machine Learning (Nice to Have)

·     ⁠Apply ML fundamentals for experiments, benchmarking, and validation.

·     Assist with model evaluation, monitoring, and performance analysis.

·     Contribute to NLP or predictive modeling initiatives when relevant.

·     Support experimentation with fine-tuning, adapters, or domain-specific models.

## Required Qualifications

·     1–2 years of professional experience in AI, software engineering, data engineering, or machine learning.

·     Bachelor's degree in Computer Science, AI/ML, Data Science, Software Engineering, or a related field.

·     Strong Python programming skills.

·     Practical experience building with LLMs, AI APIs, prompting techniques, and structured outputs.

·     Experience integrating external APIs and developing backend services.

·     Familiarity with Git, REST APIs, and software development best practices.

·     Strong written and spoken English.

·     Ability to work in a collaborative, client-focused environment.

·     Based in Kathmandu.

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## Preferred Qualifications

·     Experience with agentic AI frameworks and multi-step AI workflows.

·     Hands-on experience with RAG, embeddings, vector databases, and retrieval systems.

·     Familiarity with OpenAI APIs, Anthropic APIs, open-weight models, or similar GenAI platforms.

·     Experience with workflow orchestration and tool-calling architectures.

·     Knowledge of Hugging Face, PyTorch, LangGraph, LangChain, LlamaIndex, Hermes-Agent, OpenClaw, or similar ecosystems.

·     Exposure to cloud services, containers, batch jobs, secrets management, and deployment pipelines.

·     Interest in industrial, operational, healthcare, manufacturing, or physical-AI use cases.

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## Nice to Have

·     Fine-tuning, LoRA, PEFT, or model adaptation techniques.

·     ⁠Dashboarding, notebooks, or stakeholder-facing AI demonstrations.

·     Prior experience in energy, healthcare, or manufacturing domains.

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## What You'll Gain

·     Direct experience building production-oriented Generative AI and Agentic AI systems.

·     Mentorship from senior engineers and domain specialists.

·     Exposure to the complete lifecycle from discovery and prototyping through deployment and knowledge transfer.

·     A clear growth path toward Mid-Level AI Engineer and ownership of AI products and workflows.