Position overview

We are seeking a Senior AI Lead with deep expertise in Deep Learning, Foundation Models, and Agentic AI systems to drive our next generation of intelligent applications. You will lead a high-performing team of data scientists and ML engineers in developing AI-driven SaaS Product for Healthcare industry.

This role requires a balance of hands-on technical leadership, architectural oversight, and strategic vision to translate cutting-edge AI research into production-level solutions that deliver business value.

Key Responsibilities

• Technical Leadership: Lead the design and development of deep learning models and agent-based AI architectures for Qantev’s Healthcare Claims Data Platform.

• Research & Development: Stay at the forefront of AI advancements in areas such as transformer-based models, reinforcement learning, multi-agent systems, and LLM-based tool use.

• Agentic AI Development: Architect and deploy AI agents with capabilities including long-term memory, planning, reasoning, and autonomous tool use.

• Team Management: Mentor a team of AI scientists and ML engineers, fostering an environment of innovation and collaboration.

• Product Integration: Work cross-functionally with product, engineering, and UX teams to bring AI solutions from prototype to scalable product.

• Evaluation & Metrics: Establish benchmarks, A/B tests, and interpretability metrics for model performance and agent behavior.

• Ethics & Safety: Champion responsible AI practices, including model transparency, fairness, and compliance with Privacy & Security policies & practices.

Qualifications

Required:

• S. or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or related field.

• 6+ years of experience in AI/ML development, with a strong track record in deep learning.

• Expertise in building and deploying models using PyTorch, TensorFlow, or JAX.

• Experience with transformer architectures, diffusion models (e,g. Gemini Diffusion) and reinforcement learning.

• Proven experience with agent frameworks (e.g., LangGraph SmolAgent, Swarn).

• Experience with LLMOps - (e.g. Langsmith, Langfuse)

• Strong understanding of knowledge graphs, planning systems, memory modules, and retrieval-augmented generation (RAG).

• Experience leading AI research or applied ML teams.

• Strong software engineering skills, including experience with large-scale ML pipelines.

Preferred:

• Experience in deploying AI solutions in cloud environments (AWS, GCP, Azure).

• Familiarity with human-in-the-loop systems, simulation environments, and evaluation benchmarks for autonomous agents.

• Experience in aligning agentic behavior with safety and interpretability constraints.

Nice to Have:

• Familiarity with open-source foundation models (e.g., LLaMA, Mistral, Qwen, Gemma, Phi) and fine-tuning them for agent tasks.

• Experience in InsurTech or Healthcare Industry.

Soft Skills:

• Be Pro-active, Product minded and Business driven.

• Strong leadership and team-building skills with a proven ability to inspire, motivate, and develop data scientists & ML engineers.

• Excellent problem-solving, analytical, and troubleshooting skills.

• Strong written and verbal communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

• Ability to work in a fast-paced, dynamic environment, managing multiple priorities and deadlines.

• Screening interview (30min)

• Quantitative Interview (1h)

• Coding / System Design Interview (1h)

• Leadership Interview (1h)