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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.
Job Responsibility:
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
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
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
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
Requirements:
Expert proficiency with LLM SDKs, ML frameworks like PyTorch or TensorFlow (Keras is welcome)
mastery of LangChain and LangGraph is a plus
Strong hands-on experience with Python, SQL, Docker, and Microservices architecture
Experience with Kubernetes is a plus
A solid fundamental understanding of Mathematics and Statistics (Linear Algebra, Probability, and Statistical Significance) that underpins modern neural networks
Proven experience managing workloads within a public cloud (AWS, GCP, Azure, etc.) ecosystem
Practical experience building in HIPAA or GDPR/CCPA compliant environments
Effective Communication
Leadership and Mentorship
Problem-Solving Attitude
Collaboration and Teamwork
Adaptability and Flexibility
Nice to have:
mastery of LangChain and LangGraph is a plus
Experience with Kubernetes is a plus
What we offer:
competitive compensation and performance-based incentives
opportunities for professional growth through workshops and certifications