The posting
At IBM Consulting UK FutureNow, you’ll build a career at the forefront of hybrid cloud and AI, working with leading clients across the public and private sectors.
You’ll collaborate with top industry professionals, gain hands on experience with cutting edge technologies, and deliver solutions that create real business impact. From day one, you’ll work on meaningful, high profile programmes that stretch your skills and accelerate your growth.
We invest heavily in you—supporting continuous learning, in demand skills development, and long term career progression. You’ll thrive in a flexible, inclusive environment that values curiosity, encourages reinvention, and recognises what makes you unique.
We offer:
- Tools and policies to support your work-life balance from flexible working approaches, sabbatical programs, paid paternity leave, maternity leave and an innovative maternity returners scheme
- More traditional benefits, such as 25 days holiday (in addition to public holidays), private medical, dental & optical cover, online shopping discounts, an Employee Assistance Program, life assurance and a group pension plan through salary sacrifice.
As a Consulting AI Engineer, you'll help clients turn emerging AI capabilities into practical, secure, and production-ready solutions.
Working within IBM Consulting's Hybrid Cloud & Data practice, you'll design, build, integrate, and deploy AI-powered applications that solve real business challenges across Public Sector and regulated industry clients.
This role is ideal for engineers who enjoy building and integrating AI systems into existing business processes, platforms, and services. You'll work alongside Data Scientists, Architects, Software Engineers, and client stakeholders to deliver solutions that are scalable, secure, and trusted.
Core Responsibilities
- Design, develop, and deploy AI-powered applications and services using Large Language Models (LLMs).
- Build Retrieval-Augmented Generation (RAG) solutions and agent-based workflows for real-world business use cases.
- Integrate AI capabilities into existing enterprise applications, services, and operational processes.
- Develop APIs, services, and integration patterns that enable secure adoption of AI technologies.
- Work with Data Engineers, Architects, and client stakeholders to translate business requirements into production-ready solutions.
- Support the evaluation, testing, and optimisation of AI systems, balancing performance, cost, reliability, and risk.
- Contribute to responsible AI adoption through appropriate governance, security, and evaluation practices.
- Participate in Agile delivery teams and contribute throughout the full delivery lifecycle.
- Commercial experience developing solutions using Large Language Models (LLMs) and LLM APIs.
- Hands-on experience implementing production RAG solutions and/or agent-based AI systems.
- Strong Python development skills.
- Experience developing APIs and integrating systems using modern integration patterns.
- Understanding of prompt engineering, retrieval strategies, and AI evaluation approaches.
- Experience mitigating hallucinations and improving response quality through grounding, retrieval, or evaluation techniques.
- Understanding of Responsible AI principles, governance, and secure AI adoption.
- Strong communication skills and ability to work directly with technical and non-technical stakeholders.
- Experience delivering solutions within Agile development environments
This role is subject to pre-employment screening in line with the UK Government’s Baseline Personnel Security Standard (BPSS). An additional range of Personal Security Controls referred to as National Security Vetting (NVS) may apply, this could include meeting the eligibility requirements for The Security Check (SC) or Developed Vetting (DV).
- Experience with frameworks such as:
- LangChain
- LangGraph
- Semantic Kernel
- LlamaIndex
- Similar orchestration frameworks
- Experience with vector databases or semantic search technologies.
- Experience deploying solutions into cloud environments.
- Experience working within Public Sector, Defence, Financial Services, or other regulated environments.
- Exposure to CI/CD, containerisation, and modern software engineering practices.
- Experience mentoring junior engineers or supporting less experienced team members.



