Sr. AI & Data Engineer

Navigate competing stakeholder priorities, escalating conflicts or dependencies when needed.

Build and maintain working relationships with client stakeholders, staying up to date on industry trends and emerging technologies and applying technical judgement about where a technology may or may not be useful to a client project.

Represent the team's work clearly and credibly in client-facing settings, including presenting findings to technical audiences.

Mentor and develop junior team members, providing feedback on discrete technical topics, such as a specific component, and recognizing when to stop or escalate an activity.

Advocate for and encourage others to use best practices in software development lifecycle practices and source control (Git).

Maintain and model a professional presence and create an inclusive environment where team members can perform at their best.

Demonstrate an understanding of firm commercials and participate in the business development lifecycle, including contributing to proposals and sales pursuits, developing content, supporting pricing, and participating in technical demonstrations to explain products, workflows, screens, and solution operation.

Contribute to internal capability development and knowledge management by sharing your expertise, client experience, and project resources.

Maintain accurate and timely operational data, such as timesheets and project updates, as the foundation for good decision-making across the firm. Coach others on why it is important.

Use AI tools to support and accelerate work. Apply critical thinking to all prompts and AI-generated outputs, understand the risks of taking AI output at face value, and take full ownership of everything produced, regardless of how it was generated.

Quality-control the output of AI-assisted and agentic software development, including your own work and that of more junior colleagues.

Prior experience in management consulting, professional services, or an equivalent advisory or project-based environment.

Technical expertise in at least one Data & AI capability, such as Data Engineering, AI Engineering, Machine Learning Engineering, Python Development, or SQL Engineering.

Ability to apply solution design and architecture concepts to technical delivery.

Advanced understanding of how to apply embeddings, vector search, RAG architectures, AI implementation patterns, and machine learning workflows.

Demonstrated experience owning and delivering a workstream or defined body of work, with accountability for the outcome.

Ability to understand a client's business challenges, shape solutions, and bring structure to undefined situations.

Interest in bridging technical and non-technical communication by explaining delivered solutions at a high level to non-technical stakeholders, with coaching.

Experience facilitating workshops, client-facing working sessions, or presenting software externally.

Interest and experience in leading or mentoring junior colleagues, ideally with evidence of developing others' technical knowledge or championing best practices.

Exposure to or interest in contributing to proposals and sales pursuits.

Track record of delivering outcomes in ambiguous or evolving situations.