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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Consulting Senior Associate: AI and Automation (Entry Level) - **Company:** ERM - **Location:** Manchester, UK - **Experience:** Starter - **Salary:** £82,092.0 - **Contract:** Permanent contract - **Skills:** Microsoft Windows, Artificial Intelligence, Microsoft Azure, Data Infrastructure, Python (Programming Language), Parsing, Power BI, Microsoft SharePoint, SQL Databases, Microsoft Power Automate, Large Language Models, Multi-Agent Systems, Generative AI, Microsoft Fabric, Data Lakes, Data Analytics, Virtual Agents - **Published:** September 6, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5872113227 ## About the Role * Degree (or equivalent) in a sustainability-related, environmental, engineering, scientific or quantitative discipline, with demonstrable analytical and data-driven capability; 1-2+ years of consulting, technical, data or related experience. * Strong hands-on development skills in Python and SQL, with practical experience building data and AI pipelines end-to-end (ingestion * transformation * modelling * delivery). * Working proficiency in Microsoft Fabric - Lakehouse, Delta Lake, notebooks, Dataflows Gen2 and pipelines - in line with ERM's strategic adoption of the integrated Fabric Data Platform. * Strong Power BI skills, including semantic modelling, DAX, and the design of executive-ready dashboards and reports for non-technical audiences. * Demonstrable experience applying LLMs and/or ML to real workflow problems - e.g. document extraction, classification, summarisation, retrieval-augmented generation (RAG), structured output generation. * Familiarity with the wider Microsoft 365 and Power Platform ecosystem - Copilot extensibility, Power Automate, SharePoint/OneDrive, and Microsoft Graph - and how to compose them into low-friction business solutions. * Awareness of Agentic AI concepts (e.g. tool-use agents, planner-executor patterns, multi-agent orchestration) and a clear appetite to develop hands-on agent-building skills within the role. * Product mindset: comfort with requirements gathering, stakeholder engagement, MVP scoping and iterative delivery - whether evidenced through formal training (e.g. a recognised AI/product apprenticeship, ongoing or completed) or applied project experience. * Awareness of AI governance and Responsible AI frameworks (EU AI Act, ISO/IEC 42001, NIST AI RMF or equivalent) and a practical approach to embedding them in delivery - for example, requiring AI systems to cite verbatim sources and explain their reasoning as a baseline observability pattern. * Excellent written and spoken English; ability to translate technical concepts for non-technical audiences, including senior client stakeholders. * Right to work in the UK. * Direct experience in capital-projects, infrastructure, energy or environmental consulting - particularly Technical Due Diligence (TDD), ESDD, owner's engineering or lender's advisory engagements - with an understanding of the document types, deliverable formats and client expectations specific to those workstreams. * Experience designing and delivering training, workshops, lunch-and-learns or enablement programmes to upskill technical and non-technical colleagues on AI/automation tools. * Familiarity with Intelligent Document Processing (IDP) techniques - layout-aware parsing, table extraction, OCR pipelines, and downstream LLM-based structuring of unstructured documents. * Exposure to LLM evaluation and observability practices - e.g. eval harnesses, output guardrails, LLM-as-judge patterns, or production-grade frameworks such as Azure AI Foundry's evaluation suite - with appetite to develop these as a discipline within the role. * Working knowledge of at least one other European language, useful for engaging with EMEA project teams and clients. * Active engagement with internal or external technical communities - e.g. ERM's AI Champions network, internal Teams communities of practice, technical blogs, or open-source contributions in AI/ML. * Current or recent participation in a recognised AI/product apprenticeship or structured programme (e.g. "AI for Business Value" or similar) - including exposure to product management, stakeholder engagement, requirements gathering and AI governance. ## Description * Design, build and maintain AI-powered data and document pipelines on Microsoft Fabric (Lakehouse, Delta tables, notebooks, Dataflows Gen2, pipelines) supporting CPD service lines. * Apply Large Language Models (LLMs) to real consulting workflow problems - including document extraction, classification, summarisation, retrieval-augmented generation (RAG), and structured output generation from technical reports. * Develop Intelligent Document Processing (IDP) capabilities for the long-form, table-heavy, multi-format documents that characterise TDD, ESDD, owner's engineering and lender's advisory engagements. * Build Power BI dashboards and semantic models that translate AI/automation outputs into executive-ready insight for internal stakeholders and clients. * Explore and prototype Agentic AI patterns (tool-use agents, planner-executor, multi-agent orchestration) for consulting workflows where they offer step-change value. * Embed Responsible AI practice into every solution - including source citation, verifiable reasoning, output guardrails and alignment with frameworks such as the EU AI Act, ISO/IEC 42001 and the NIST AI RMF. * Drive adoption of AI and automation tooling across CPD through training sessions, workshops, lunch-and-learns and written enablement materials. * Act as a trusted internal advisor to project managers, technical leads and Partners on where AI and automation can credibly improve delivery quality, speed or margin. * Run discovery and requirements-gathering workshops with stakeholders across CPD to identify, scope and prioritise candidate use cases. * Apply a product mindset - defining MVPs, iterating on user feedback, and managing a backlog of CPD AI/automation initiatives. * Contribute to ERM's wider AI Champions network and CPD technical communities, sharing learnings and reusable patterns across the firm. * Retain an active attachment to the TDD subteam, contributing to fee-earning client engagements (renewables, energy infrastructure and adjacent capital projects). * Identify and deliver client-facing AI/automation workstreams within TDD and broader CPD engagements - supporting proposal scoping, pricing inputs and delivery. * Apply a commercial mindset, recognising opportunities to extend or secure billable client work through differentiated AI-enabled delivery. ## Related Videos - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - 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