Description
About The Role
Our client is looking for a passionate and motivated Junior Generative AI Engineer who has 0–2 years of experience (or strong project/internship exposure) in building AI/LLM-based applications. This role is ideal for candidates who have good foundational knowledge of Generative AI, LLMs, and backend development—and want to grow into a full-stack AI engineer over time.
You will work with senior engineers and contribute to building chatbots, automation tools, RAG systems, and LLM-powered apps that solve real-world business problems. This role gives you exposure to modern AI tools, mentorship, and hands-on experience with enterprise-grade AI applications.
Key Responsibilities
- Assist in building AI/LLM-based applications such as chatbots, copilots, content generators, and workflow automation tools.
- Support the development and enhancement of RAG pipelines, embeddings, and vector search systems.
- Work on integrating AI models with backend systems using Python (FastAPI/Flask) or Node.js.
- Help implement prompt engineering, model evaluation, and fine-tuning tasks under senior guidance.
- Develop API endpoints and backend services required for AI model orchestration.
- Contribute to testing, validating, and optimizing AI outputs to reduce hallucinations and improve reliability.
- Collaborate with product, engineering, and data teams to understand requirements and deliver solutions.
- Stay updated with the latest AI tools, models, and frameworks to continuously improve your skill set.
Required Skills
- 0–2 years of experience in AI/ML, Generative AI, NLP, or software development (internships, projects, freelance work, or academic work also counts).
- Strong foundational knowledge of Python and basics of web frameworks (FastAPI/Flask).
- Basic understanding of LLMs, embeddings, vector databases (Pinecone, FAISS, Chroma, or similar).
- Familiarity with prompt engineering and working with APIs like OpenAI, HuggingFace, Cohere, etc.
- Good understanding of backend and API development fundamentals.
- Knowledge of Git, version control, and collaborative development practices.
- Curiosity and willingness to learn modern AI tech stacks like LangChain, LlamaIndex, or LangGraph.
Preferred Skills (Good to Have)
- Experience with any Generative AI project (college project, hackathon, internship).
- Basic understanding of RAG concepts and vector search.
- Exposure to Docker, cloud platforms (AWS/GCP/Azure), or MLOps concepts.
- Familiarity with multimodal AI (image, audio, video).
- Knowledge of fine-tuning techniques like LoRA/QLoRA (even theoretical understanding is fine).
Soft Skills
- Strong problem-solving ability with a willingness to experiment and iterate.
- Good communication skills to explain ideas clearly.
- Growth mindset and eagerness to learn from senior engineers.
- Ability to work in a fast-paced, dynamic environment.
- Team player attitude with a proactive approach.
