CA
Associate AI Engineer (GenAI / Agentic AI)
cremisoft ai · Not specified · onsite · Posted 5d ago
Not disclosed0–2 yrsfulltimeSourced from
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About this role
About Cremisoft AI
Cremisoft AI builds GenAI and agentic AI solutions that help businesses automate work and make better decisions. We're a growing team, and we're looking for early-career engineers who want to learn production-grade AI engineering from day one.
About the Role
We're hiring an Associate AI Engineer (0–2 years of experience, freshers and recent graduates welcome) to help build GenAI and agentic AI applications. You'll work under the guidance of senior engineers on LLM integration, RAG pipelines and AI agents, and contribute to real features from your first weeks.
Responsibilities
• Build and test LLM-powered features such as chatbots, RAG pipelines and simple agents, with guidance from senior engineers
• 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 what works and what doesn't
• 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
• Take part in code reviews, stand-ups and sprint planning
• Document your work clearly so others can follow it
Required Qualifications
• Bachelor's degree in Computer Science, Data Science, Engineering or a related field
• 0–2 years of experience (internships and academic projects count)
• Solid foundation in Python and basic data structures and algorithms
• Exposure to machine learning or NLP fundamentals through coursework, projects or internships
• Basic understanding of how LLMs work (tokens, embeddings, prompting)
• Familiarity with Git and basic software engineering practices
• Strong analytical thinking and eagerness to learn in a fast-moving field
Preferred Qualifications
• Personal or academic projects involving LLMs, chatbots or GenAI APIs (a hackathon project counts)
• Exposure to any LLM API (OpenAI, Anthropic, Hugging Face) or a vector database
• Familiarity with basic ML concepts such as supervised learning, embeddings and evaluation metrics
• Any cloud exposure (free-tier AWS, Azure or GCP counts)
• Open-source contributions, Kaggle competitions or a GitHub portfolio
What Success Looks Like
• You're curious and coachable, ask good questions and take feedback well
• Within 3–6 months, you ship small, well-tested features independently with code review support
• Within your first year, you own a full RAG pipeline or agent workflow end to end
• You communicate clearly and document 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 from day one
• Learning and development budget for courses and certifications
• Clear growth path with regular feedback
Hiring Process
1. Application and profile review
2. Short technical screening call
3. Hands-on assignment or technical interview (Python and GenAI basics)
4. Final conversation with the team
To stand out, include a link to your GitHub or a project where you've used an LLM API.
Cremisoft AI builds GenAI and agentic AI solutions that help businesses automate work and make better decisions. We're a growing team, and we're looking for early-career engineers who want to learn production-grade AI engineering from day one.
About the Role
We're hiring an Associate AI Engineer (0–2 years of experience, freshers and recent graduates welcome) to help build GenAI and agentic AI applications. You'll work under the guidance of senior engineers on LLM integration, RAG pipelines and AI agents, and contribute to real features from your first weeks.
Responsibilities
• Build and test LLM-powered features such as chatbots, RAG pipelines and simple agents, with guidance from senior engineers
• 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 what works and what doesn't
• 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
• Take part in code reviews, stand-ups and sprint planning
• Document your work clearly so others can follow it
Required Qualifications
• Bachelor's degree in Computer Science, Data Science, Engineering or a related field
• 0–2 years of experience (internships and academic projects count)
• Solid foundation in Python and basic data structures and algorithms
• Exposure to machine learning or NLP fundamentals through coursework, projects or internships
• Basic understanding of how LLMs work (tokens, embeddings, prompting)
• Familiarity with Git and basic software engineering practices
• Strong analytical thinking and eagerness to learn in a fast-moving field
Preferred Qualifications
• Personal or academic projects involving LLMs, chatbots or GenAI APIs (a hackathon project counts)
• Exposure to any LLM API (OpenAI, Anthropic, Hugging Face) or a vector database
• Familiarity with basic ML concepts such as supervised learning, embeddings and evaluation metrics
• Any cloud exposure (free-tier AWS, Azure or GCP counts)
• Open-source contributions, Kaggle competitions or a GitHub portfolio
What Success Looks Like
• You're curious and coachable, ask good questions and take feedback well
• Within 3–6 months, you ship small, well-tested features independently with code review support
• Within your first year, you own a full RAG pipeline or agent workflow end to end
• You communicate clearly and document 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 from day one
• Learning and development budget for courses and certifications
• Clear growth path with regular feedback
Hiring Process
1. Application and profile review
2. Short technical screening call
3. Hands-on assignment or technical interview (Python and GenAI basics)
4. Final conversation with the team
To stand out, include a link to your GitHub or a project where you've used an LLM API.
Sourced from foundit
Skills
Prompt EngineeringLLM Integrationvector databasesRAG PipelinesGenAI frameworksHugging Face Transformersmodel servingPythonData ProcessingAPI IntegrationLangchainAgentic AiGIT