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)
