AI Engineer

Responsibilities:

• Fine-tune and adapt pre-trained LLMs (e. g., GPT, Claude, Mistral, LLaMA) for domain-specific tasks using APIs and lightweight fine-tuning frameworks.
• Design and evaluate high-quality prompts for language understanding, summarization, reasoning, and conversational use cases.
• Implement Retrieval-Augmented Generation (RAG) pipelines using tools like LangChain, LlamaIndex, or custom logic.
• Work with vector databases (e. g., Pinecone, Weaviate, FAISS) to enable contextual retrieval and memory for LLM-based systems.
• Build proof-of-concept AI applications using no-code/low-code tools and platforms (e. g., Zapier, Make, Streamlit, Gradio).
• Monitor and evaluate LLM outputs, optimize for accuracy, consistency, and latency.
• Collaborate with product and business teams to convert requirements into intelligent, AI-driven workflows.

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• 2+ years of experience in AI, NLP, or software development roles.
• Hands-on experience fine-tuning or customizing LLMs using APIs or lightweight libraries (e. g., Hugging Face PEFT, LoRA, OpenAI fine-tuning).
• Strong understanding of prompt engineering and few-shot techniques.
• Proficiency with Python and relevant AI tooling (e. g., LangChain, OpenAI, Anthropic, Cohere APIs).
• Familiarity with cloud platforms (AWS/GCP/Azure) and deploying AI solutions in production environments.
• Knowledge of structured and unstructured data formats (JSON, CSV, PDFs, web scraping, etc. ).

Nice to Have:

• Experience with building chatbots, virtual assistants, or AI copilots.
• Exposure to MLOps-lite tools or automation tools (e. g., Dify, Flowise, AutoGen, Dust, etc. ).
• Comfort working with APIs, webhooks, and RESTful services.
• Basic understanding of ethics, safety, and bias in AI systems.