AI Solutions Engineer
Sabio
contract
Posted on:
Location Type: Hybrid
Location: London • United Kingdom
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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 & Tools
Pythongenerative AILLMsREST APIscloud native engineeringCI CDtesting strategyconversational AIorchestration frameworksvector databases
Soft Skills
strong communication skillsstakeholder engagementquality mindsetmanaging ambiguityiterative deliverydesign decisionsprogress reportingteam collaborationproblem solvingadaptability