Job Description

Overview:

Lead the design and development of GenAI-powered systems, including LLM apps, RAG pipelines, fine-tuning strategies, and model deployment.

Own architectural decisions, code quality, and system scalability in AI-heavy projects.

Guide the team in using tools like OpenAI, Hugging Face, LangChain, Pinecone/Weaviate, and model optimization libraries.

Manage the full ML lifecycle:

from data preparation and model experimentation to deployment and monitoring in production.

Collaborate with Product Managers, Designers, and Stakeholders to define and prioritize AI use cases.

Coach and mentor team members in technical growth, GenAI trends, and engineering excellence.

Stay abreast of the latest GenAI research (e.g., GPT-4/Claude/Mistral/Sora) and translate those insights into practical applications

Responsibilities:

6+ years of software engineering or ML experience with at least 2+ years leading teams or projects.

Hands-on experience with LLMs (GPT, LLaMA, Claude, etc.) and GenAI frameworks (LangChain, LlamaIndex, etc.).

Deep proficiency in Python, APIs, ML pipelines, and cloud platforms (AWS/GCP/Azure).

Solid understanding of vector databases (FAISS, Pinecone, Weaviate), embeddings, and RAG architecture.

Experience with fine-tuning, prompt engineering, and/or RLHF workflows.

Excellent communication, leadership, and stakeholder management skills.

Requirements:

Background in NLP, multimodal models (text + image/video/audio), or knowledge distillation.

Experience building GenAI chatbots, copilots, or domain-specific AI assistants.

Familiarity with DevOps/MLOps:

Docker, Kubernetes, MLflow, CI/CD, or model monitoring.

Contributions to AI research or open-source GenAI tools/projects.