Client Name: Confidential

ABOUT THE BLACK BOX TALENT (TBBT)

The Black Box Talent (TBBT) is a talent acquisition and executive search firm helping organizations identify, attract, and hire high-quality professionals across diverse industries and geographies.

We partner closely with our clients to understand their business, culture, and hiring requirements, enabling us to deliver targeted, relevant, and quality talent for critical positions.

Our approach combines industry-focused recruitment expertise, strong candidate networks, structured sourcing, and personalized talent solutions to support organizations in building high-performing teams.

POSITION OVERVIEW

The Lead Data Scientist / Lead AI Engineer is a hands-on leadership role responsible for designing, developing, deploying, and scaling production-grade AI solutions while mentoring a team of AI engineers and data scientists.

The ideal candidate will have extensive experience building end-to-end AI systems, implementing advanced ML models, and developing Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, fine-tuning, and AI agents.

KEY RESPONSIBILITIES

• AI/ML Architecture & Strategy: Lead AI/ML and Generative AI architecture, design, development, deployment, and overall strategy.
• Generative AI Development: Design and implement solutions using LLMs, RAG, prompt engineering, fine-tuning, and AI agent frameworks.
• End-to-End AI Systems: Build scalable AI systems covering data pipelines, model training, evaluation, deployment, monitoring, and continuous improvement.
• Applied ML & Analytics: Apply Machine Learning and Deep Learning for forecasting, predictive analytics, recommendations, automation, and optimization.
• Team Leadership: Mentor AI engineers and data scientists while collaborating with Product, Engineering, and business teams.
• Governance & Quality: Ensure AI solutions meet scalability, reliability, quality, and Responsible AI standards while staying updated with emerging technologies.

CANDIDATE PROFILE

• 5–8 years of AI/ML experience, including leadership responsibility.
• Strong foundation in Machine Learning, Deep Learning, and Statistical Modeling.
• Proficiency in Python, SQL, Pandas, NumPy, Scikit-learn, PyTorch, and TensorFlow.
• Hands-on experience with OpenAI, Anthropic, and open-source LLMs.
• Strong experience in Prompt Engineering, RAG, Fine-tuning, and AI Agents.
• Proven experience in forecasting, predictive modelling, recommendation systems, stakeholder management, and end-to-end AI solution delivery.
• Preferred exposure to AWS, Azure, or GCP.
• Preferred experience with MLOps, Spark/Hadoop, and vector databases such as Pinecone, FAISS, Weaviate, or ChromaDB.
• Exposure to AI Governance, Responsible AI, Security, and Compliance is preferred.