Hybrid AI Solutions Engineer

at Sabio

• Job title: AI Solutions Engineer
• Job type: Contract
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: No Education Requirement
• Tech skills: Cloud, Python
• Location requirements: Hybrid, London, United Kingdom

About the role

• AI Solutions Engineer delivering customer facing AI solutions as part of Sabio Group's project teams. Building AI solutions integrated with broader systems and supporting iterative delivery in dynamic environments.

Responsibilities

• Deliver customer facing AI solutions as part of a project delivery team, owning engineering tasks from design through build, test, release, and handover.
• Build agentic AI solutions and concepts aligned to customer use cases, including tool use, orchestration, planning and execution loops, and workflow automation.
• Rapidly develop proof of concepts, prototypes, and MVPs to validate value, then evolve them into production ready solutions where required.
• Engineer and integrate AI capabilities into broader systems including APIs, services, data sources, identity and access, observability, and operational tooling.
• Translate requirements into clear technical deliverables, including estimates, dependencies, risks, and implementation approaches.
• Apply strong software engineering discipline including clean code, testing, version control, code review, documentation, and secure coding practices.
• Support customer workshops and delivery ceremonies, communicating design decisions, trade offs, and progress to technical and non technical stakeholders.
• Implement appropriate guardrails and responsible AI controls covering privacy, safety, transparency, auditability, and human oversight.
• Contribute to delivery acceleration through reusable components, templates, reference implementations, and internal tooling improvements.

Requirements

• Mid to senior level software engineering experience with strong hands on capability in Python and or another modern language, producing production quality code.
• Practical experience building solutions using generative AI and LLMs, including prompt and flow design, retrieval augmented generation, tool and function calling, evaluation, and iteration.
• Experience applying agentic AI patterns such as multi step orchestration and tool usage, planning and execution workflows, state management, and safety approaches appropriate to the use case.
• Experience delivering within a customer project environment, including managing ambiguity, iterative delivery, deadlines, and stakeholder engagement.
• Strong integration skills including REST APIs, authentication and authorisation concepts, error handling, performance, and reliability considerations.
• Familiarity with cloud native engineering principles in a platform agnostic way, including environments, configuration, CI CD, logging and monitoring, and secrets management.
• Strong communication skills, able to explain technical concepts and decisions clearly to mixed audiences.
• A quality mindset covering testing strategy, maintainability, documentation, and operational considerations.
• Experience with Cognigy or similar conversational AI and intelligent automation platforms.
• Experience in conversational AI, contact centre, or customer experience automation use cases.
• Familiarity with agent and LLM frameworks and tooling, including orchestration frameworks, vector databases, and evaluation tooling.
• Awareness of governance and assurance practices such as prompt security, data privacy, model evaluation, red teaming, and audit trails.
• Experience building reusable accelerators to improve delivery speed and consistency across projects.