Associate AI Engineer (GenAI / Agentic AI)

About Cremisoft AI

Cremisoft AI builds GenAI and agentic AI solutions.

About the Role

We are hiring an Associate AI Engineer to help build GenAI and agentic AI applications. You will work under the guidance of senior engineers on LLM integration, RAG pipelines, and AI agents.

Key Responsibilities

• Build and test LLM-powered features such as chatbots, RAG pipelines, and simple agents.
• Write clean, well-tested Python code for data processing, API integration, and model-serving components.
• Prepare and clean datasets for embeddings, fine-tuning, and evaluation.
• Experiment with prompt engineering and document findings.
• Support testing and evaluation of AI features, including accuracy checks, regression testing, and basic monitoring.
• Learn and apply GenAI frameworks and tools (LangChain, Hugging Face, vector databases) with team mentorship.
• Participate in code reviews, stand-ups, and sprint planning.
• Document work clearly.

Requirements & Tech Stack

• Solid foundation in Python and basic data structures and algorithms.
• Familiarity with Git and basic software engineering practices.
• Basic understanding of how LLMs work (tokens, embeddings, prompting).
• Experience with GenAI frameworks and tools (e.g., LangChain, Hugging Face, vector databases) is a plus.
• Experience with any LLM API (e.g., OpenAI, Anthropic, Hugging Face) is a plus.
• Exposure to any cloud (e.g., AWS, Azure, GCP) is a plus.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
• 0–2 years of experience (internships and academic projects count).
• Exposure to machine learning or NLP fundamentals through coursework, projects, or internships.
• Strong analytical thinking and eagerness to learn.
• Personal or academic projects involving LLMs, chatbots, or GenAI APIs (a hackathon project counts) are preferred.
• Familiarity with basic ML concepts (e.g., supervised learning, embeddings, evaluation metrics) is preferred.
• Open-source contributions, Kaggle competitions, or a GitHub portfolio are preferred.

What Success Looks Like

• Curiosity, coachability, good questions, and receptiveness to feedback.
• Shipping small, well-tested features independently with code review support within 3–6 months.
• Owning a full RAG pipeline or agent workflow end-to-end within the first year.
• Clear communication and documentation of experiments and decisions.

Growth Path

Associate AI Engineer → AI Engineer → Senior AI Engineer

What We Offer

• Competitive entry-level salary.
• Fully remote role within India.
• Structured onboarding and mentorship from senior AI engineers.
• Hands-on work on production GenAI systems.
• Learning and development budget for courses and certifications.
• Clear growth path with regular feedback.

Hiring Process

• Application and profile review.
• Short technical screening call.
• Hands-on assignment or technical interview (Python and GenAI basics).
• Final conversation with the team.