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.

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.
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.
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

(ref:hirist.tech)

Taazaa - Senior AI/ML Engineer