AI Agent Platform Engineer

1 week ago

Noida, Uttar Pradesh, India Crenovent Full time

Job Title: AI Agent Platform Engineer

Location: Noida

Department: Product Engineering – RevAi Pro

Role Overview

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.

Key Responsibilities

1. Agent Architecture & Runtime

  • 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

2. LLM Integration & Prompt Engineering

  • 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.

3. Backend API & Microservices Development

  • 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

4. Data Integration & Task Routing

  • 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

5. DevOps, Monitoring, and Scaling

  • 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

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