AI Engineer
Summary
The AI Engineer will build and deploy agentic AI tools and workflow automations to improve efficiency within a financial services firm. The role involves working with LLMs like Claude, developing MCP servers, and managing the full lifecycle of AI agents from development to production.
- Designing, building, and deploying AI-powered tools, agents, and workflow automations for
use across the firm.
- Working hands-on with the Claude ecosystem - Cowork, Claude Code, Connectors, Skills, and
Plugins - alongside other AI platforms (ChatGPT, Gemini, and others).
- Owning the end-to-end deployment lifecycle for AI tools and agents, including packaging,
testing, hosting, and monitoring in production.
- Collaborating with teams across the firm to identify opportunities to automate repetitive or
manual processes using AI and workflow orchestration tools.
- Reviewing and validating AI-generated outputs to ensure accuracy, completeness, and
reliability before they reach internal or client-facing use.
- Staying current on evolving AI capabilities and evaluating new tools and platforms for potential
adoption.
- Documenting technical approaches clearly and communicating outcomes to both technical
and non-technical stakeholders.
- Exercising sound judgement across AI workflows: assessing which client and fund data may be
sent to which model, working exclusively through approved endpoints and enterprise tooling,
and upholding the confidentiality obligations expected in a financial services environment.
- Complying with IT policies and procedures.
- Maintaining the security of information at all times.
Requirements
- AI Tools & LLMs - Hands-on experience using platforms such as Claude, ChatGPT, Gemini, or
Copilot, with the prompt-engineering skill to get consistent, high-quality outputs across
models.
- Agents and MCP - Hands-on experience building agentic workflows and integrating external
tools through MCP servers or equivalent tool-use frameworks. Alongside this, a systematic
approach to validating model output: maintained eval sets, regression checks before release,
and structured human review loops, rather than ad-hoc spot checking.
- Demonstrated Projects - Self-built AI projects or agents you can showcase, covering both
standard and custom workflow-specific use cases. Projects built with Claude (Cowork, Claude
Code, Connectors, Skills, Plugins) are particularly valued.
- Prompt Engineering - Ability to structure prompts effectively - framing tasks clearly, refining
outputs, and adapting instructions to get consistent, high-quality results across different AI
models.
- Build & Deploy - Experience taking an AI tool or agent from build to production; packaging
(Docker), hosting, and monitoring in a real environment.
- Technical Skills - Python for scripting, API calls, and data pre-processing; SQL for querying
structured data; React for simple internal dashboards; AI coding tools such as Claude Code or
ChatGPT Codex.
- Communication & Collaboration - Good communication skills, with the ability to work
effectively across teams and explain technical work clearly to non-technical stakeholders
- Bachelor’s or Master’s degree in computer engineering, Computer Science, or any other
relevant specialization (e.g., AI/ML, Data Science, IT).
- 1+ years of relevant experience in AI/ML engineering, software development, or applied AI
projects.
- You should be able to clearly demonstrate how you have used AI tools - including Claude - to
build, deploy, and improve efficiency, quality, or speed in a professional context.