Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this AI Integration Lead role.

Rezi rewrites your resume against BlueCrest Capital Management's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the AI Integration Lead posting at BlueCrest Capital Management — free, in seconds.

About the Role

The Front Office AI Technology Team develops and supports enterprise-grade AI capabilities, including LLM-powered applications, RAG systems, and internal AI tooling. This role focuses on enabling and integrating AI solutions, providing training, understanding business processes, prototyping, and reporting on adoption to ensure AI is used effectively, reliably, and securely across the firm.

Responsibilities

Act as a go-to point of contact for teams seeking to understand and effectively use available AI tools.
Run workshops, demos, and hands-on sessions to illustrate the benefits of LLMs and emerging AI technologies.
Support the day-to-day adoption of AI tools like Microsoft Copilot, ChatGPT, and Claude within real workflows.
Deliver practical training on prompt engineering, AI limitations, and best usage patterns.
Create and maintain reusable training materials, including prompt examples, walkthroughs, and guidance notes.
Continuously refine training content based on user feedback and emerging best practices.
Collaborate with teams to understand existing processes, pain points, and areas for AI application.
Help teams articulate problems clearly for effective AI tooling application.
Map simple end-to-end workflows and identify opportunities for AI assistance.
Build simple prototypes or proof-of-concept workflows using Python, internal libraries, or approved AI APIs.
Pair with engineers or platform teams for ideas that extend beyond quick prototypes.
Focus on delivering small, shippable improvements rather than large, speculative solutions.
Collect structured feedback on AI tool effectiveness, user challenges, and areas of friction.
Share insights with AI Tech, governance, and Infrastructure Tech teams to guide tooling, documentation, and prioritization.
Help surface recurring themes and trends from user feedback.
Support the definition and tracking of adoption metrics for internal AI tools.
Assist in maintaining reports and dashboards that illustrate usage and engagement patterns.
Monitor adoption trends and identify areas needing additional enablement, training, or tooling adjustments.
Combine quantitative usage data with qualitative user feedback to understand practical AI tool application.
Share regular adoption insights with stakeholders to inform prioritization of training, documentation, and AI tooling improvements.

Requirements

Demonstrated interest in evolving applied AI technologies and their practical application in improving business processes in a controlled manner.
Experience delivering or supporting training, workshops, or enablement sessions for technical and non-technical audiences.
Hands-on experience using modern AI tools beyond typical end-user interaction.
Practical understanding of prompt engineering techniques and common LLM failure modes.
Experience grounding AI outputs in data (e.g., through document retrieval, APIs, MCP, or structured context).
Exposure to designing AI-assisted workflows that support repeatable tasks.
Familiarity with enterprise and low-code AI tooling, such as Microsoft Power Apps, Power Automate, Copilot Studio, Claude Cowork, or similar platforms.
Practical experience assessing AI output quality and limitations for business use cases.
Ability to iterate prompts or workflows to improve reliability.
Comfortable working with Python at a practical level (scripts, APIs, data handling).
Strong communication skills, with the ability to explain technical concepts clearly to non-technical users.
Comfortable operating in environments with evolving requirements and iterating pragmatically.
Familiarity with retrieval-augmented generation (RAG) concepts at a practical level.
Experience designing or supporting simple AI-assisted workflows for document handling, summarisation, data extraction, or knowledge access.
Awareness of responsible AI considerations in regulated environments, including data handling, output validation, and human review.
Exposure to lightweight agent-style patterns (e.g., tool use, structured outputs, task decomposition).

Skills

Applied AI technologies
AI integration
LLMs
RAG systems
Prompt engineering
AI limitations
AI usage patterns
Workflow mapping
Prototyping
Python
AI APIs
MS Copilot Studio
Adoption metrics
Reporting
Data analysis
User feedback collection
Communication
Problem-solving
Adaptability
Collaboration

Location

Front Office

Work Type

Full-time

Experience Level

Mid-level

About the Company

The Front Office AI Technology Team sits within the Front Office Technology department and provides a shared capability for the development, operation, and adoption of AI across the firm.
We develop the core AI foundations required to deploy AI safely and at scale, while also working closely with the business to ensure these capabilities are used effectively in day-to-day workflows.
The team balances innovation with discipline, providing common tooling, patterns, and guidance that allow AI to be used consistently and responsibly across research and operational contexts.
The firm is investing heavily in modern AI platforms and tools.
BlueCrest is committed to providing an inclusive environment for its workforce.

Equal Opportunity

As an employer, we provide equal opportunities to all people regardless of their gender, marital or civil partnership status, race, religion or ethnicity, disability, age, sexual orientation or nationality.