Applied AI and Agentic Automation Consultant

Applied AI and Agentic Automation Consultant

The opportunity

We are developing a community of experienced practitioners who can turn applied-AI ambition into secure, usable and measurable operational capability. The work sits where business process, data, software engineering, architecture, risk and human decision-making meet. It is not about demonstrations for their own sake. The objective is to identify the right intervention, shape a robust solution and carry it from proof of value through testing, secure deployment and operational use.

You may work as an individual specialist, lead a focused workstream or contribute within a multidisciplinary team. We value people who combine hands-on technical depth with the consulting judgement needed to work through ambiguity and connect technology to outcomes.

What you will do • Structure ambiguous business and operational challenges into clear AI use cases, decisions and delivery priorities. • Translate business needs into AI products, services, workflows and architecture that can scale beyond a prototype. • Design and deliver applied AI, GenAI or agentic solutions through discovery, proof of value, MVP, architecture, build, integration, evaluation, deployment and continuous improvement. • Engineer reliable connections to enterprise data, APIs, tools, workflows, user experiences and operational systems. • Design human oversight, exception handling, permissions, policy controls, auditability, escalation, safety controls and recovery from the outset. • Establish robust evaluation, monitoring and observability for quality, grounding, retrieval, reliability, cost, latency, security and business value. • Apply appropriate software-engineering, MLOps, LLMOps or AgenticOps practices, including testing, version control, release management and reusable architecture patterns. • Translate technical choices and limitations into clear implications for senior, technical and non-technical stakeholders. • Connect the solution to measurable operational outcomes and support adoption into live ways of working.

Essential evidence • At least five years of relevant AI, data, software, automation, architecture, transformation or consulting delivery. • A specific applied-AI, GenAI or agentic system that you personally helped design, build, integrate, govern or deploy beyond training and isolated experimentation. • Strong practical evidence in at least one delivery lane: production RAG; tool or function calling; agent workflows or orchestration; multi-agent systems; MCP or comparable integration patterns; AI-enabled workflow automation; enterprise AI architecture and integration; or full-stack AI-product delivery. • Evidence of implementation using relevant technologies such as Python, TypeScript or JavaScript, SQL, model APIs, LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, OpenAI Agents, Azure OpenAI, AWS Bedrock, Google Vertex AI or credible equivalents. • Evidence of connecting AI to enterprise data, APIs, business processes, user interfaces or operational systems. • Evidence of evaluation, observability, monitoring, guardrails, human review, failure handling, security, privacy or responsible-AI controls. • Evidence of a structured delivery lifecycle such as Agile, SDLC, MLOps, LLMOps, AgenticOps, DevSecOps, architecture governance, evaluation gates or a credible hybrid approach. • The ability to explain the context, your personal contribution, the important technical decisions, production-readiness work and operational outcome.

Consulting mindset and delivery

You should listen before prescribing, bring structure to uncertainty, communicate difficult ideas accessibly and challenge assumptions constructively. You should be credible with engineers and senior stakeholders, take ownership of outcomes and adapt when evidence changes. Consulting behaviours support the assessment but do not replace hands-on delivery evidence.

Useful additional experience • AI governance, responsible AI, security, regulated delivery or policy-controlled autonomous workflows. • Process intelligence, workflow automation or operational-data analysis. • Microsoft Power Platform or Copilot Studio, ServiceNow AI and automation, SAP, UiPath or other enterprise platforms. • Model or vendor evaluation, cost and latency optimisation, reference architecture, enterprise search or knowledge orchestration. • Public-sector, systems-integrator or complex-enterprise delivery. • Proposal shaping, client workshops, capability development or team leadership.

How evidence will be assessed

A title, certification, course, prompt-engineering claim, strategy document or isolated prototype alone is insufficient. Strong evidence identifies the operational problem, architecture or platform, personal contribution, engineering and integration work, evaluation and controls, production or production-readiness evidence and resulting use or value. A strong prototype-to-MVP practitioner may remain relevant, but a production-proven practitioner will score higher.

About Team Inspire

BeInspired is a Technology, Transformation & Growth delivery partner. Through Team Inspire, we mobilise specialist consultants and multidisciplinary teams to deliver critical workstreams and complex programmes. We start with the outcome, understand the capability gap and shape the right response around it.

This is a UK capability-building opportunity for future contract, interim and consultancy assignments. It is not confirmation of a specific assignment. Start date, duration, day rate, IR35 status, location, working pattern and screening requirements will be confirmed for each requirement. Contractor status, availability, rate and clearance will be qualified separately and never inferred.

Security and eligibility

Some assignments may require BPSS, Security Check clearance or other client screening. Existing clearance is useful when current and verifiable but is not a universal requirement. Nationality, residency, clearance eligibility and right to work must not be inferred from location or employment history.