freehire launches on Product Hunt on 26 August.

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AI Engineer

Summary

Build and deploy AI agents and automation workflows for enterprise use, integrating with internal systems and data platforms using Python, RAG, and cloud infrastructure.

You will design, build, deploy, evaluate, and operate enterprise AI agents and automation workflows. You will integrate agents with internal systems and data platforms, implement RAG and evaluation pipelines, monitor production behavior, and maintain security, governance, auditability, and safeguards.

Responsibilities

  • Design and implement AI agents for multi-step workflows
  • Build single-agent and multi-agent architectures
  • Develop reusable agent patterns and templates
  • Deploy agents on managed AI platforms
  • Configure secure execution environments and session handling
  • Design human-in-the-loop escalations and approval gates
  • Own prompt and configuration versioning, rollouts, and canary releases
  • Integrate agents with internal data platforms, APIs, and services
  • Implement RAG pipelines, vector databases, and knowledge layers
  • Build evaluation frameworks for accuracy, completion, and reliability
  • Monitor agent behavior and production performance
  • Implement fallback mechanisms, error handling, cost controls, and guardrails
  • Maintain security compliance, audit trails, and explainability
  • Implement safeguards against hallucinations, unsafe actions, and data leakage
  • Translate business workflows into agent-driven automation

Requirements

  • Python programming
  • Experience with LLM applications and agent systems
  • Familiarity with LangChain, LangGraph, AutoGen, or CrewAI
  • Experience with API development, microservices, and tool orchestration
  • Knowledge of vector databases, RAG pipelines, and prompt engineering
  • Experience with AWS, Azure, or GCP
  • Docker and Kubernetes
  • CI/CD, production deployment, and observability tooling
  • Experience designing goal-driven AI systems and multi-step reasoning workflows
  • Ability to implement evaluation pipelines and production guardrails
  • Awareness of LLM cost, latency, and performance trade-offs

Benefits

  • Flow Academy
  • Opportunities to attend domain-related conferences
  • Daily catered lunch
  • Coffee, stocked kitchen, and snack bar
  • In-house bar and lounge
  • Company boat
  • In-house gym
  • Nutritionist or personal trainer sessions
  • Bi-weekly massages
  • Annual company trip
  • Company events
  • Global office rotations
  • Annual discretionary profit share
  • Comprehensive benefits

See also

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