Agentic AI Senior Consultant

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Agentic AI Senior Consultant based in United Kingdom. In this role, you will act as a trusted technical advisor and hands-on engineering expert, helping enterprise customers design, implement, and scale advanced agentic AI solutions. You will lead the entire customer delivery lifecycle, from identifying high-value business opportunities and designing multi-agent architectures to deploying production-ready systems. Combining strong software engineering expertise, applied AI knowledge, and event-driven architecture experience, you will transform AI concepts into secure, scalable, and reliable enterprise applications. You will work closely with customer engineering teams, business stakeholders, and internal product specialists to accelerate the adoption of intelligent automation. Your responsibilities will also include establishing best practices for agent development, evaluation, monitoring, and governance while mentoring other technical professionals. This is an opportunity to work at the forefront of enterprise AI innovation within an international, customer-focused, and technically ambitious environment. Accountabilities: - Own the technical success of enterprise customers' agentic AI initiatives, managing the complete delivery lifecycle from initial discovery and solution design through development, production deployment, ongoing operations, and advisory services. - Lead customer workshops to identify, assess, and prioritize high-value agentic AI use cases, translating business objectives into measurable and technically achievable workflows. - Design and implement sophisticated multi-agent architectures, including agent decomposition, orchestration, task delegation, tool integration, memory management, state handling, and human-in-the-loop controls.

- Develop, review, and troubleshoot production-quality software using Go or Python, building agents, plugins, tools, and integrations that meet enterprise requirements. - Deploy and operate agentic AI applications using Docker, Kubernetes, and major cloud platforms, ensuring scalability, reliability, and maintainability. - Integrate AI agents with enterprise applications, data sources, and legacy systems through MCP servers, A2A protocols, REST APIs, and event-driven messaging architectures. - Implement retrieval-augmented generation (RAG), vector databases, knowledge bases, embeddings, and real-time event context strategies to improve agent accuracy and access to relevant information. - Apply the Agent Development Lifecycle (ADLC) throughout solution delivery, covering requirements gathering, architecture design, evaluation pipelines, testing, version control, release management, monitoring, and operational documentation. - Establish robust observability, security controls, governance frameworks, and responsible AI practices for agentic systems, including tracing, quality evaluation, cost and latency monitoring, access control, and auditability. - Advise customers on large language model selection and optimization across providers such as Anthropic, OpenAI, Google, AWS Bedrock, and Azure AI Foundry, considering prompt engineering, token consumption, costs, and model performance trade-offs. - Act as a long-term technical advisor, identifying opportunities for further AI adoption and helping customers progress from isolated pilots to enterprise-wide, event-driven AI implementations. - Conduct recurring technical reviews, solution health checks, and roadmap discussions aligned with customer priorities and annual planning cycles. - Enable customer engineering teams to independently operate, maintain, and extend implemented solutions through technical workshops, collaborative development sessions, and comprehensive documentation.