Our Consulting team at BearingPoint is dedicated to optimizing client business operations through advanced ERP and CRM systems. With deep expertise in SAP across various domains like finance, logistics, data, and technology, we streamline processes and enhance decision-making efficiency. Our proficiency in Salesforce helps us improve customer relationships with innovative strategies. We leverage data tools like PowerBI for insightful analytics and excel in Microsoft cloud technologies, particularly Azure, to provide secure and scalable solutions. Additionally, our team develops integrated mobile front-end and back-end applications, ensuring user-friendly mobile access to ERP and CRM systems.

BearingPoint's consulting services are designed to deliver tailored solutions that meet the unique needs of each client, driving growth and operational excellence. We pride ourselves on our client-centric approach, focusing on delivering measurable results and sustainable improvements.

As a member of the Agent Lab architecture group, you hold end-to-end ownership of a defined portfolio of AI assets. You lead their architecture from initial design through production and ongoing evolution, and collaborate with fellow architects to ensure consistency, interoperability and reuse across the Agent Lab portfolio.

Your mission in this role is to own the architecture and technical direction of the Agent Lab assets assigned to you: AI agents, multi-agent systems, Copilot-based solutions, GenAI platforms and their enterprise integrations. Take them from proof of concept to products and offerings clients can run in production.

You act as the architecture authority for your assets and as a peer within the Agent Lab architecture group. Together, the group defines shared standards, conducts peer design reviews and ensures that every solution delivered is secure, scalable, maintainable and aligned with clear business outcomes.

Primary Functions and Tasks:

AI & agent architecture

Define the target architecture and roadmap for the assets you own.

Design multi-agent systems: orchestration patterns, memory strategies, knowledge containers, tool calling and agent-to-agent collaboration.

Keep a clear decision record for your assets, and contribute to the Lab's shared reference architectures and reusable frameworks.

Track emerging AI technologies and bring adoption proposals to the architect group.

Generative AI & Copilot solutions

Lead solution design on Azure AI Foundry, Azure OpenAI and Azure AI Search, and where relevant Copilot Studio and Microsoft 365 Copilot.

Define proven patterns for RAG and enterprise search, prompt orchestration, human-in-the-loop workflows, connectors and MCP-based tool integration.

Set the approach for evaluation, observability and cost control of LLM and agent workloads in production.

Enterprise solution architecture

Translate business needs into scalable, supportable solutions.

Define integration strategies with SAP, Salesforce, ServiceNow, other ERP and CRM platforms, and custom APIs.

Architect how Agent Lab applications are hosted and run on Azure: compute (for example App Service, Container Apps, Functions), networking, identity, secrets, monitoring, scaling and cost.

Define deployment and environment standards: infrastructure as code, CI/CD pipelines, environment separation, and handover to operations or the client's IT team.

Take part in the Agent Lab architecture board: present your designs and review those of other architects, so assets stay consistent and can work together.

Security, compliance & AI governance

Agent Lab solutions handle client data and act autonomously, so security and regulatory compliance are conditions for release, not later checks. You are accountable for the following on every asset you own:

Involve client and internal IT and Security teams in each solution from the first design session, through review and go-live, and again at every significant change.

Apply the EU AI Act: classify each solution by risk level, identify obligations such as transparency, human oversight, logging, data governance and technical documentation, and design them in from the start.

Ensure compliance with GDPR and applicable client, sector and data-residency requirements, including data protection impact assessments where needed.

Run threat modelling and security design reviews covering AI-specific risks: prompt injection, data leakage, excessive agent permissions, insecure tool and connector access, and model misuse.

Apply least-privilege access, identity and secrets management (Entra ID), data classification and sensitivity labelling (Microsoft Purview), and auditable logging of agent actions.

Keep the evidence trail needed for audits and client due diligence: architecture decisions, risk assessments, test results and sign-offs.

Hold the right to stop a release that does not meet security or compliance requirements, and escalate through the architecture group.

Help define the Lab's shared security and compliance baseline and keep it current as regulation and threats change.

Team & delivery leadership

Lead the developers and consultants working on your assets on a day-to-day basis: assign and prioritise work, provide technical direction and unblock the team. Line management stays with their respective managers.

Take accountability for delivery: plan the work with the team, set realistic timelines, and ensure milestones and deadlines are met.

Track progress, identify risks and blockers early, and escalate with proposed solutions when scope, quality or timelines are at risk.

Ensure delivery quality through design and code reviews, agreed engineering practices and testing standards.

Report progress to stakeholders, clients and Agent Lab management, and manage expectations on scope, effort and timing.

Review the team's designs and implementation approaches.

Support presales for your assets: solution shaping, estimates, client workshops and executive conversations.

Mentor team members technically and build capability across the Lab through pairing and knowledge sharing.