Agentic AI Advisor - Venture Capital Firm

Description:

This is a strategic role with a niche fund representing a set of private investors. The role would be responsible for deploying, monitoring, and optimizing autonomous AI agents in seed-stage startups to deliver business value, performance metrics and disciplined execution.

The work would involve a few hours per week for nearly 2 months for each startup against mentorship equity in those startups. The advisor would be able to create a portfolio of equity in startups by putting a few hours every weekend. Depending on the quality of his work, some startups might be able to offer a full-time CTO role to the advisor.

Work to be done:

- To design, build, and deploy autonomous software systems that can perceive their environment, reason, plan, and take actions to achieve specific goals with minimal human intervention.

- To create simple AI agents using existing building blocks, uncomplicated prompt engineering and minimal customization to handle multi-step workflows, access external tools/APIs, and maintain memory across interactions.

- To use data scrapping tools like Apollo.io to populate the AI agents with easily available market data.

Skills needed:

- Must respect speed of execution and basic timelines.

- Mindset: A "builder" mentality, comfortable with ambiguity, and able to transition from "cool demo" to enterprise-grade reliability.

- Experience: 2 to 5+ years in software development, machine learning, or AI engineering.

- Technical Understanding: Proficiency in using AI agent platforms, API integrations, prompt engineering, and basic understanding of Python or data analysis tools.

- Strategic Thinking: Ability to map business problems to AI-driven solutions.

- Testing & Evaluation: Running simulations in sandboxes to validate agent performance, ensure safety, and minimize agent errors like hallucinations.

- Multi-Agent Coordination: Designing systems where multiple specialized agents collaborate to complete complex, long-running tasks.

- Tool Integration: Connecting AI agents to external systems (APIs, databases, data scrapping tools, CRM systems like Salesforce, Slack, Apollo.io) to retrieve data and execute tasks.

- Programming: Proficiency in Python (most common), JavaScript, or TypeScript.

- AI Frameworks: Experience with LangChain, LlamaIndex, AutoGen, CrewAI, or Microsoft Semantic Kernel.