AI Solutions Engineer
Sabio
contract
Posted on:
Location Type: Hybrid
Location: London • 🇬🇧 United Kingdom
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
CloudPython
About the role
- 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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
Pythongenerative AILLMsREST APIscloud native engineeringCI CDtesting strategyconversational AIorchestration frameworksvector databases
Soft skills
strong communication skillsstakeholder engagementquality mindsetmanaging ambiguityiterative deliverydesign decisionsprogress reportingteam collaborationproblem solvingadaptability