Senior AI/ML Engineer

• Collaborate with product leaders, business analysts and subject matter experts to identify and shape high-value AI opportunities
• Design and deliver end-to-end AI and Machine Learning solutions, from data preparation and model development through to deployment and monitoring
• Build and maintain robust MLOps frameworks, governance processes and engineering best practices
• Develop Generative AI and Agentic AI solutions, including RAG, semantic search, AI agents, multi-agent workflows and LLM orchestration frameworks
• Work with LangGraph, Google ADK, Microsoft Agent Framework, LlamaIndex and similar tools
• Deploy AI solutions across Azure, GCP and Snowflake
• Embed responsible AI principles, evaluation frameworks, safety controls and assurance mechanisms throughout the AI lifecycle
• Integrate external AI services and APIs into enterprise applications
• Act as an AI ambassador within the business
• Coach and mentor junior colleagues and support capability development
• Promote engineering standards, quality assurance and coding best practice
• Work within Agile delivery teams where appropriate
• Ensure compliance with regulatory requirements and maintain high standards of data security and governance

Requirements

• Proven experience designing, building and deploying AI/ML solutions from concept through to production
• Strong experience implementing MLOps strategies, frameworks and operational best practices
• Deep understanding of Generative AI and Agentic AI concepts, including RAG architectures, embeddings and vector search, evaluation frameworks, and LLM orchestration
• Hands-on experience with LangChain, LangGraph, LlamaIndex, CrewAI, Autogen, Google ADK, or similar modern AI frameworks
• Experience developing and deploying AI solutions on Azure AI Foundry, Azure AI Studio, AKS, Google Vertex AI, Cloud Run, Snowflake Cortex AI, or Snowpark
• Strong software engineering skills including Python, CI/CD pipelines, GitHub Actions, Azure DevOps, Docker, and Kubernetes
• Experience working with APIs and integrating external AI services
• Ability to engage, influence and build relationships with technical and non-technical stakeholders
• Experience mentoring and developing colleagues
• Familiarity with Agile delivery methodologies and tools such as Azure DevOps
• Experience working within healthcare, insurance or other highly regulated industries is desirable
• Bachelor's degree in Computer Science, Mathematics, Statistics or another quantitative discipline is desirable
• Master's degree in Data Science, Statistics, Epidemiology or a related field is desirable

Core Competencies

Demonstrates expertise in designing, building, and deploying AI and Machine Learning solutions, with a strong focus on MLOps frameworks and responsible AI principles. Proficient in integrating AI services and APIs while ensuring compliance with regulatory standards in highly regulated industries.

Highest-signal resume keywords

• AI/ML Solution Design and Deployment
• MLOps Strategies and Frameworks
• Generative AI and Agentic AI Expertise
• Software Engineering Skills in Python
• Agile Delivery Methodologies

Hard Skills

• AI/ML Solution Development
• MLOps Implementation
• Generative AI Concepts
• Python Programming
• CI/CD Pipelines
• API Integration
• Data Preparation
• Model Development
• Deployment and Monitoring
• Evaluation Frameworks

Soft Skills

• Stakeholder Engagement
• Coaching and Mentoring
• Collaboration
• Influencing Skills
• Relationship Building

Certifications & Qualifications

• Bachelor's Degree in Computer Science
• Master's Degree in Data Science

Industry Keywords

• Healthcare
• Insurance
• Regulatory Compliance
• Data Security
• Governance

Tools & Technologies

• LangChain
• LangGraph
• LlamaIndex
• Google ADK
• Azure AI Foundry
• Azure DevOps
• Docker
• Kubernetes
• Snowflake
• Google Vertex AI

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