AI Agent Platform Engineer

You will be responsible for designing, developing, and scaling the AI Agent Framework that powers automation-first modules in RevAi Pro, such as Tell Me, Action Center, and intelligent AI agents. This role is critical to shaping the core foundation of how automation, enterprise search, and just-in-time execution work inside our platform. Architect and implement the core orchestration engine for AI agents (event-driven/task-based). Manage agent lifecycle functions such as spawn, pause, escalate, and terminate. Enable secure, real-time communication between agents, services, and workflows. Integrate memory and retrieval systems using vector databases like Pinecone, Weaviate, or Qdrant. Integrate LLM providers (OpenAI, Azure OpenAI, Anthropic, Mistral, etc.) into agent workflows. Create modular prompt templates with retry/fallback mechanisms. Implement chaining logic and dynamic tool use for agents using LangChain or LlamaIndex. Develop reusable agent types such as Summarizer, Validator, Notifier, Planner, etc. Develop FastAPI-based microservices for agent orchestration and skill execution. Create APIs to register agents, execute agent actions, and manage runtime memory. Implement RBAC, rate limiting, and security protocols for multi-tenant deployments. Build connectors to integrate structured (CRM, SQL) and unstructured data sources (email, docs, transcripts). Route incoming data streams to relevant agents based on workflow and business rules. Support ingestion from tools like Salesforce, HubSpot, Gong, and Zoom. Deploy the agent platform using Docker and Kubernetes on Azure. Implement Redis, Celery, or equivalent async task systems for agent task queues. Set up observability to monitor agent usage, task success/failure, latency, and hallucination rates. Create CI/CD pipelines for agent modules and prompt updates. Ideal Candidate Profile: - 2-4 years of experience in backend engineering, ML engineering, or agent orchestration. - Strong command over Python (FastAPI, asyncio, Celery, SQLAlchemy). - Experience with LangChain, LlamaIndex, Haystack, or other orchestration libraries. - Hands-on with OpenAI, Anthropic, or similar LLM APIs. - Comfortable with vector embeddings and semantic search systems. - Understanding of modern AI agent frameworks like AutoGen, CrewAI, Semantic Planner, or ReAct. - Familiarity with multi-tenant API security and SaaS architecture. - Bonus: Frontend collaboration experience to support UI for agents and dashboards. - Bonus: Familiarity with SaaS platforms in B2B domains like RevOps, CRM, or workflow automation. What You'll Gain: - Ownership of agent architecture inside a live enterprise-grade AI platform. - Opportunity to shape the future of AI-first business applications. - Collaboration with founders, product leaders, and early enterprise customers. - Competitive salary with potential ESOP. - First-mover engineering credit on one of the most advanced automation stacks in SaaS.,