Ai Ml Engineer

AI Engineer:

Project Intel

• Forward-Deployed AI Engineering
• Partner directly with bankers to identify and prioritize high-impact AI use cases across deal workflows
• Agentic Workflow Development
• Build and deploy multi-step AI agents to improve productivity across sourcing, execution, and analysis
• AI-Generated Deal & Marketing Materials
• Automate creation of pitch decks, CIMs, and other client-facing content using AI
• Claude Skills, Plugins & Data Integration
• Develop domain-specific AI skills and connect them to internal data sources using MCP and plugins
• Financial Modeling Augmentation
• Enhance and streamline banker modeling workflows with AI-assisted analysis
• Rapid Prototyping & Productionization
• Deliver solutions in short iterative cycles and scale successful use cases into production
• AI-Driven Prospecting
• Build workflows to identify and prioritize target companies and opportunities
• Product-Led Execution
• Execute against a structured backlog, translating requirements into technical solutions under product leadership

Experience

• 35+ years in data/engineering roles, with 3+ years focused on AI engineering
• Proven track record of deploying and scaling agentic systems in production
• Experience working in regulated environments with governance and security constraints

Required Skills (Priority Order)

• Agentic Application Development Hands-on experience building multi-step agents, tool-use patterns, and prompt chaining using frameworks such as Anthropic SDK, LangChain, Microsoft Agent Framework, and Pydantic AI
• Claude Ecosystem Expertise Experience developing Claude Skills, plugins, connectors, and Cowork agents in production environments
• Cross-Platform Agent Development – Ability to migrate and adapt agent workflows across platforms (e.g., Claude Copilot Studio)
• MCP Integration – Experience building MCP servers, integrating tools/data sources, and managing authentication and response handling
• Python – Strong proficiency for AI/ML application development and system integration

Key Responsibilities

• Design and deploy multi-step agentic workflows in production environments (not just POCs)
• Build AI-powered solutions supporting investment banking workflows (deal sourcing, company matching, pitch materials, financial modeling augmentation)
• Develop and integrate Claude-based agents, skills, connectors, and plugins
• Implement secure, governed AI systems with appropriate guardrails for regulated environments
• Build and integrate MCP servers to connect LLMs with internal tools and data sources
• Translate product requirements into technical implementations in partnership with product leadership
• Act as a forward-deployed engineer, collaborating directly with bankers to identify and prioritize AI use cases
• Rapidly prototype and productionize solutions in iterative cycles (weeks to days)