Senior AI Engineer

N-iX is looking for Senior AI Engineer for one of our clients.
Our client is a precision mental health company on a mission to make high-quality, evidence-based digital mental health support accessible at scale.
Their platform transforms deep clinical expertise into trusted, personalized, and measurable digital experiences that help people improve their mental wellbeing. Working with digital health partner companies across the US, they combine AI, rigorous clinical science, and human-centered design to deliver meaningful real-world outcomes.

This is a high-ownership, high-impact role. We operate to the highest standards of clinical safety, compliance, and reliability, because the people using our platform are managing real mental health challenges.

Key Responsibilities:

• Design, build, and maintain agentic AI systems, including multi-agent orchestration frameworks (e.g. LangGraph) for digital therapy product
• Lead the migration of conversational AI bot architecture from legacy frameworks to modern agentic frameworks, improving developer velocity and feature extensibility.
• Develop and maintain fast inference service integrations to reduce end-to-end message latency and enable more responsive AI-powered interactions.
• Work closely with AI scientists and researchers to translate research prototypes into robust, production-grade software.
• Monitor AI models in production — build telemetry and observability tooling to ensure reliability and quality.
• Disseminate and instil good engineering practice, whilst able to work effectively alongside scientists who may be less focused on engineering rigour.
• Manage and mentor other engineers, supporting their technical growth and development.
• Stay current with developments in AI engineering — particularly around LLMs, agentic systems, and LLMOps — and advocate for their adoption where they can meaningfully improve our platform or engineering processes.
• Work effectively in a cross-functional team, collaborating closely with Product, QA, DevOps, Data, AI, and Engineering stakeholders
• Communicate confidently in a multinational environment with business, engineering, marketing, and clinical stakeholders when needed
• Participate fully in Agile/Scrum ceremonies and contribute to continuous improvement
• Troubleshoot complex issues, perform root-cause analysis, and investigate new tools and approaches
• Identify delivery bottlenecks, technical risks, and improvement opportunities proactively
• Help balance delivery speed, quality, scalability, maintainability, and technical debt across initiatives

Requirements:

• Agile thinker, able to work with evolving and underspecified requirements
• Proven ability to deliver software in complex, fast-moving environments.
• Strong programming skills and experience building production software systems.
• Experience with LLMs, generative AI, or modern AI engineering (including prompt engineering, LLM APIs, or agentic frameworks). 
• Enthusiasm for and comfort with the rapid changes happening in software engineering driven by AI — including AI-assisted development tools and evolving engineering practices.
• Proven ability to mentor and support others, to ‘see the bigger picture’, and make pragmatic engineering trade-offs.
• A desire to make a meaningful difference — our mission is to improve access to mental health care.
• An interest in working with data and understanding how AI systems can be safely and effectively deployed in clinical contexts.
• Solid production experience with Microsoft Azure
• Strong understanding of version control, security best practices, and Agile methodologies
• Strong Agile delivery experience with focus on speed and quality
• Startup mindset: adaptable, fast-moving, pragmatic
• Result-oriented mindset with ownership mentality
• Excellent communication and collaboration skills, able to lead conversations and drive alignment
• Able to work independently and as part of a team
• Proactive, responsive, and dependable with strong ownership mindset

Technical Stack/Tools:

• Cloud: Azure
• Data & Storage: Azure SQL, Cosmos DB, Blob Storage, Azure Storage 
• DevOps, Infrastructure & CI/CD: Azure DevOps, GitHub, Azure Pipelines, Docker, Kubernetes, Terraform, Grafana

Nice to have:

• Experience with agentic frameworks such as LangGraph, LangChain, or similar.
• Experience building or working with coding agents or AI-assisted development tooling.
• Experience deploying and operating LLMs or ML models in production (LLMOps / MLOps). 
• Experience with Azure cloud services, including Azure ML, Azure Kubernetes Service (AKS), or Azure DevOps.
• Experience with message broker systems and real-time data pipelines.
• Experience working in a regulated environment (e.g. healthcare, finance, or with HIPAA and GDPR).
• Experience delivering software in a research or clinical environment. 
• BSc or higher in Computer Science, Mathematics, or a related field.
• Testing and test automation experience
• Data engineering experience