Description :

We are looking for a Senior AI/ML Engineer for our AI initiatives. You will be part of a very fast moving team distributed across the globe. You will bridge the gap between high-level AI research and industrial-grade production systems.

This is a role for a T-Shaped engineer : someone with deep expertise in LLMs, machine learning and mathematics, but with the broad proficiency across DevOps, databases, and microservices needed to turn experimental models into stable, scalable products. As a senior member of the team, you will drive Engineering Excellence, setting up the architectural benchmarks that allow our AI solutions to be resilient, compliant, and market-ready.

1. What you'll do AI Orchestration & Agentic Systems :

- Design and implement complex, stateful agentic workflows using LangGraph and LangChain.

- Implement tool calling and Model Context Protocol (MCP) to securely connect models to diverse data sources and tools.

- Optimize high-throughput model serving using vLLM or similar high-performance engines.

Engineering Excellence & Mentorship :

- Establish and enforce high-quality coding standards and modular architectural patterns across the AI stack.

- Lead by example through rigorous code reviews and hands-on technical guidance, fostering a culture of technical rigor and production readiness.

Data Engineering & Database Design :

- Architect scalable database schemas (SQL, NoSQL, and Vector) optimized for RAG, hybrid search, and real-time analytics.

- Build and maintain robust data pipelines that ensure high data quality for model training and evaluation.

Platform, MLOps & Compliance :

- Own the containerization (Docker/Kubernetes) and deployment of AI workloads on public and private clouds.

- Ensure all systems meet strict regulatory requirements, including HIPAA, GDPR, and CCPA.

- Implement MLOps practices, including automated testing for AI outputs and performance monitoring.

2. Your qualifications Technical Frameworks :

- Expert proficiency with LLM SDKs, ML frameworks like PyTorch or TensorFlow (Keras is welcome); mastery of LangChain and LangGraph is a plus.

Systems :

- Strong hands-on experience with Python, SQL, Docker, and Microservices architecture. Experience with Kubernetes is a plus. Math & Stats : A solid fundamental understanding of Mathematics and Statistics (Linear Algebra, Probability, and Statistical Significance) that underpins modern neural networks.

Cloud :

- Proven experience managing workloads within a public cloud (AWS, GCP, Azure, etc.) ecosystem.

- Regulatory : Practical experience building in HIPAA or GDPR/CCPA compliant environments.

3. Behavioral :

- Here are five essential behavioral skills Artificial Intelligence (AI) Lead should possess :

Effective Communication :

- Clearly and concisely convey ideas, requirements, and feedback to team members, stakeholders, and clients, fostering an environment of open dialogue and mutual understanding.

Leadership and Mentorship :

- Inspire and guide the development team, providing support and encouragement, while promoting a culture of continuous learning and improvement.

Problem-Solving Attitude :

- Approach challenges with a proactive mindset, quickly identifying issues and developing innovative solutions to overcome obstacles.

Collaboration and Teamwork :

- Work well within a team, encouraging collaboration and valuing diverse perspectives to achieve common goals and deliver high-quality results.

Adaptability and Flexibility :

- Stay adaptable in a fast-paced, dynamic environment, effectively managing changing priorities and requirements while maintaining focus on project objectives