AI Developer - LLM

Key Responsibilities:

- Architect the Agentic Stack: Design, develop, and maintain multi-agent systems and LLM-powered workflows tailored for marketing and sales automation.

- Bridge Strategy & Tech: Translate high-level marketing and sales goals into technical requirements, prompt chains, and autonomous agent behaviors.

- Data Integration & Pipelines: Connect AI agents with internal data sources, CRMs (HubSpot, Salesforce), marketing automation tools, and external APIs to ensure real-time contextual awareness.

- Experimentation & Optimization: Treat prompt engineering and agent behavior as a science. Continually test, benchmark, and iterate on agent performance, accuracy, and conversion metrics.

- Project & Lifecycle Management: Oversee the deployment lifecycle of AI agents from ideation to production, ensuring robust error handling, guardrails, and compliance.

What We Are Looking For:

- The "Builder" Mindset: A rare blend of part Engineer (coding and architecture), part Strategist (understanding customer funnels and conversion), and part Data Scientist (analyzing model performance and data structures).

- Technical Proficiency: Experience with AI orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen) and building production-grade solutions using OpenAI, Anthropic, or open-source LLMs.

- Development Skills: Strong programming skills in Python or Node.js, and experience working with REST APIs, webhooks, and vector databases (e.g., Pinecone, Chroma).

- Domain Knowledge: A solid grasp of B2B/B2C marketing funnels, sales pipelines, lead scoring, and marketing technology (MarTech) ecosystems.

- Execution & Ownership: Ability to manage complex technical projects independently in a fast-paced, remote environment.