AI Engineer (LLMs & Generative AI)

Position: AI Engineer (LLMs & Generative AI)

Overview:

Key Responsibilities:

• Design, build, and optimize LLM-based applications using frameworks such as Hugging Face, OpenAI APIs, LangChain, or similar.
• Develop and maintain RAG pipelines, including embeddings generation, vector databases, retrieval strategies, and prompt orchestration.
• Fine-tune and adapt language models for specific use cases, balancing performance, cost, and latency.
• Implement model evaluation, monitoring, and optimization using well-defined quality and performance metrics.
• Build and experiment with AI agent frameworks (e.g., LangGraph, CrewAI, AutoGen, AgentKit) for multi-step reasoning and workflows.
• Collaborate with cross-functional teams to translate product requirements into AI solutions.
• Stay up to date with the latest advancements in LLMs, GenAI tooling, and best practices, and apply them to ongoing projects.

Required Skills & Qualifications:

• Strong foundation in Machine Learning, NLP, and Python programming.
• Practical experience with PyTorch, Hugging Face Transformers, and modern LLM workflows.
• Hands-on experience building applications using OpenAI or similar LLM platforms.
• Experience working with LangChain (or equivalent frameworks) and vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma).
• Ability to take ML/AI projects from experimentation to production-ready prototypes.
• 1–2 years of professional or equivalent hands-on experience, including strong personal or open-source projects in NLP/LLMs.

Nice to Have:

• Exposure to deployment workflows (APIs, Docker, cloud platforms).
• Experience with prompt engineering, evaluation frameworks, or observability tools for LLMs.
• Familiarity with cost optimization and latency tuning for LLM-based systems.

Ideal Candidate: