GenAI Engineer

Role Overview:

We are looking for a skilled Generative AI Engineer to join our client's team to build intelligent systems powered by large language models (LLMs) and other generative AI architectures. This role involves developing and deploying LLM-based features, integrating vector search, fine-tuning models, and collaborating closely with product and engineering teams to deliver robust, scalable GenAI applications.

You will work across the entire GenAI stackfrom prompt design to inference optimizationand play a key role in shaping how generative models are applied in real-world products.

Responsibilities:

• Fine-tune and deploy LLMs (e.g., GPT, LLaMA, Mistral) using frameworks such as Hugging Face Transformers and LangChain.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging vector databases like Pinecone and FAISS.
• Engineer prompts to ensure structured and reliable outputs for use cases including chatbots, summarization, and coding copilots.
• Implement scalable inference pipelines and optimize latency, throughput, and costs via techniques such as quantization and model distillation.
• Collaborate with product, design, and frontend teams to integrate GenAI features into user-facing applications.
• Monitor, evaluate, and iteratively improve model performance, safety, and accuracy in production environments.
• Ensure compliance with privacy, safety, and responsible AI practices (e.g., content filtering and output sanitization).

Required Skills:

• Strong programming skills in Python and familiarity with modern ML tooling.
• Practical experience with LLM frameworks (Hugging Face Transformers, LangChain, LlamaIndex).
• Experience building or deploying RAG pipelines, including managing embeddings and vector search.
• Solid understanding of transformer architectures, prompt engineering, and tokenization.
• Hands-on experience with APIs like OpenAI, Anthropic, Cohere, and model serving frameworks (FastAPI, Flask).
• Experience deploying ML models using Docker, Kubernetes, and/or cloud platforms (AWS, GCP, Azure).
• Comfortable with model evaluation, monitoring, and troubleshooting inference pipelines.

Nice to Have:

• Experience with multimodal models (diffusion, TTS, image/video generation).
• Knowledge of RLHF, safety alignment, and fine-tuning best practices.
• Familiarity with open-source LLMs such as Mistral, LLaMA, Falcon, and optimization methods like LoRA or quantization.
• Experience with LangChain agents, tool usage, and memory management.
• Contributions to open-source GenAI projects or published demos/blogs.
• Exposure to frontend technologies (React/Next.js) for prototyping GenAI tools.

Educational Qualifications:

• Bachelor's or Master's degree in Computer Science, AI, Machine Learning, Data Science, or related technical fields.
• Candidates with relevant project experience or open-source contributions may be considered regardless of formal degree.