AI Engineer

• Build and ship end-to-end AI applications (backend, data, APIs, UI)
• Turn ambiguous problems into working software quickly
• Use AI-native tools to accelerate delivery
• Apply key AI patterns (RAG, agents, prompt engineering, evaluation)
• Build and scale the AI Platform on Azure (multi-region)
• Own core components: APIM, identity, networking, observability, data
• Establish CI/CD, IaC, testing, and deployment standards
• Integrate with internal and third-party systems (CRM, CX platforms)
• Work with tools like Zendesk, Genesys, Intercom, Microsoft 365
• Build APIs, webhooks, and event-driven systems
• Embed GDPR, ISO 27001, SOC 2 (and others) into the platform
• Partner with Security/GRC on data protection and access control
• Partner with Product on roadmap and build-vs-buy decisions
• Document systems, architecture, and processes
• Monitor production systems and improve performance, cost, and reliability

Full Stack AI Engineer

AI Research Scientist

• Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage.
• Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms.
• Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint.
• Build, run, and monitor controlled inference tests in both simulated and live production environments.
• Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices.
• Document iterative results and compare outcomes against established benchmarks to validate performance across platforms.
• Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices.
• Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions.
• Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics.
• Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems.
• Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications.
• Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements.

AI Research Engineer – Kernel & Inference Optimization

• Designing and enhancing AI-powered chatbots for customer interactions in billing, sales, and technical support to reduce reliance on human agents.
• Automating business processes to improve operational efficiency using AI technologies.
• Contributing to the development and maintenance of scalable AI infrastructures and integrate new machine learning techniques and large language models (LLMs) where applicable.
• Evaluating and working with various AI models including LLMs, reasoning models, machine learning, and function calling models for different purposes.
• Contributing to the roadmap for integrating speech-to-text functionality and real-time voice APIs, especially for telephony systems.
• Working closely with other team members to evaluate and implement new AI technologies and tools, ensuring robust and reliable AI systems.
• Participating in the testing and quality assurance of AI-driven systems, ensuring accurate and efficient performance.
• Managing and maintaining AI agents across various platforms, ensuring their smooth operation and continuous improvement.

AI Engineering, Voice API

• Be part of our Global Engineering Network!
• Responsible for designing, building, and deploying next-generation AI/ML and Generative AI solutions that drive business transformation at scale.
• Own the end-to-end AI lifecycle: data ingestion, model development, deployment, and monitoring.
• Build and optimise scalable ML pipelines and services.
• Develop AI-driven automation solutions, including intelligent agents.
• Implement MLOps best practices (CI/CD, model versioning, monitoring, retraining).
• Collaborate with cross-functional teams (engineering, product, data) to deliver AI solutions.
• Translate business needs into technical AI use cases and architectures.
• Stay up to date with emerging AI trends and contribute to innovation initiatives.

Senior AI Engineer

• The AI Engineer is the technical builder within the Legal Innovation Team. The work is fundamentally applied natural language processing (NLP): extracting meaning from legal documents, classifying and comparing text, reasoning over complex material, and building systems that analyse language at scale.
• They take the specifications and requirements defined by Innovation Lawyers and turn them into working solutions: document processing pipelines, AI-powered analysis workflows and deployed systems that lawyers and clients use daily.
• This is not a generic software engineering role. The AI Engineer works exclusively on legal technology, embedded in a team that understands the domain deeply. They do not need to be a lawyer (that expertise sits with the Innovation Lawyers they work alongside) but they must build systems that meet the exacting standards legal work demands: accuracy, reliability, auditability, and data security.

AI Engineer, Legal Innovation Team

Machine Learning Engineer

• Analyze and optimize time-series sensor data to ensure real-time performance.
• Architect and deliver scalable AI/ML systems and reference designs for real-time applications.
• Build proof-of-concepts (PoCs) and pilot systems, optimizing models for latency, throughput, cost, and power efficiency.
• Develop surrogate models for large-scale device/system simulations.
• Explore innovative agentic AI approaches for system optimization and planning.

See all jobs on JobTailor

Full Stack AI Engineer

AI Research Engineer – Kernel & Inference Optimization

AI Engineering, Voice API

Senior AI Engineer

AI Engineer, Legal Innovation Team

Staff AI/ML Engineer – Edge AI System