AI/ML Engineer

Role Overview

We are looking for an AI/ML Engineer adept at designing, deploying, managing, and optimizing AI solutions, including machine learning models and agentic AI workflows, primarily leveraging Azure technologies. This position focuses on delivering scalable, secure, cost-efficient, and governed AI and ML infrastructure and applications suitable for production environments.

Key Responsibilities

• Create, implement, and optimize machine learning and large language models (LLM) solutions using platforms such as Azure Databricks, Azure ML, and Azure AI Foundry.
• Develop and sustain scalable applications powered by LLMs, ensuring robust performance and cost-effectiveness in live production settings.
• Construct and maintain agentic AI workflows for executing autonomous or semi-autonomous tasks and orchestrations.
• Manage pipelines covering the lifecycle stages of AI/ML workflows, inclusive of data preparation, experimentation, deployment, and monitoring.
• Collaborate closely with platform engineers, data scientists, data engineers, and business stakeholders to transition AI innovations from experimental phases to stable, production-ready deployments.
• Implement strategies for retrieval, prompting, tool-calling, and orchestration in enterprise AI applications.
• Develop AI services using frameworks like LangChain or LangGraph to enable multi-step reasoning and orchestrations across AI functionalities.
• Apply interoperability standards such as Model Context Protocol (MCP) for seamless tool and context integration across varied AI applications.
• Continuously monitor and refine AI models and workflows in operation to uphold quality, accuracy, and reliability.
• Adopt and apply best practices in LLMOps and MLOps that cover experimentation, version control, deployment, and lifecycle governance.
• Ensure that all AI/ML solutions adhere to cloud governance, security, compliance standards, and responsible AI guidelines.
• Document the development processes, models, and engineering patterns thoroughly to facilitate reproducibility and knowledge dissemination.
• Keep abreast of advances in AI/ML technologies, especially in LLMOps and agentic AI, implementing enhancements that upgrade existing solutions.

Candidate Profile

• Proficient in working with Azure Databricks, Azure ML, and preferably Azure AI Foundry.
• Experienced in deployment and operational management of LLMs and traditional machine learning models within enterprise cloud infrastructures.
• Familiar with MLflow for experimental tracking, model versioning, and lifecycle management for both classic ML and LLM technologies.
• Solid grasp of LLMOps including aspects like scaling, monitoring, evaluation, governance, and cost optimization.
• Practical experience developing agentic AI workflows using LangChain, LangGraph, or equivalent frameworks.
• Knowledgeable in Model Context Protocol or similar standards facilitating integration across AI tools and enterprise systems.
• Strong programming skills in Python, with experience in libraries such as PyTorch, Pydantic, LangChain, and LangSmith.
• Skilled in prompt orchestration, structured output generation, evaluation techniques, and tool-calling patterns for LLM-based applications.
• Understanding of retrieval-augmented generation (RAG) frameworks, vector search techniques, and other enterprise search and retrieval methodologies.
• Awareness of cloud governance and responsible AI practices relevant to enterprise settings.
• Experience with core Azure cloud infrastructure services such as Virtual Machines, Active Directory, Automation, etc.
• Experienced in engineering ETL pipelines and managing workflow systems with Azure Data Factory, Databricks workflows, or their equivalents.
• Proficient with container technologies (Docker) and orchestration platforms (Kubernetes).
• Competent in version control tools, particularly GitLab, complemented by CI/CD pipeline experience.
• Familiar with Agile software development practices, including sprint planning, stand-ups, and retrospectives.
• Strong understanding of data architecture, transformation processes, and integration techniques.
• Effective communicator capable of engaging both technical and non-technical audiences.
• Team-oriented, pragmatic, and committed to delivering results while supporting wider team objectives.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML Engineering, or a closely related technical discipline.
• Minimum of 5 years of professional experience in machine learning and data engineering roles.
• Demonstrable expertise with Azure Databricks and associated Azure services such as Azure ML and AI Foundry.

About the Employer

We are a global law firm dedicated to supporting our clients' ambitions worldwide. Innovation shapes how we deliver legal services, with a presence spanning the Americas, Europe, the Middle East, Africa, and Asia Pacific. Our culture fosters opportunities for career growth, personal development, and shared success. We prize diversity, inclusion, and a workplace culture where every individual’s voice is valued and respected. Flexible and agile working arrangements are embraced to accommodate employees' lives outside of work.

Pre-engagement screening checks will be conducted where legally permissible prior to commencement.