Agentic AI Engineer – Design Autonomous AI Agents

About the role

We are looking for an Agentic AI Engineer to design, build, and operate autonomous AI agents and workflow automation solutions. You will work closely with cross‑functional teams to translate business needs into reliable, production‑grade AI services.

Key responsibilities

• Design and develop agentic AI systems, including autonomous agents, tool‑using agents, multi‑agent orchestration, and workflow state machines.
• Create and maintain AI‑powered automation workflows on low‑code platforms such as n8n and Make (Integromat) to integrate business processes, data pipelines, and cross‑application tools.
• Build LLM‑driven agents capable of reasoning, planning, knowledge retrieval, and task execution across enterprise systems.
• Integrate agents with internal APIs, CRM/ERP, Jira, Confluence, Slack, email, databases, payment systems, and other tools using function calling, MCP, and A2A patterns.
• Develop end‑to‑end AI automations that combine LLM capabilities with n8n/Make workflows for tasks like document processing, lead enrichment, support triage, reporting, and data synchronization.
• Implement safety guardrails, content filters, policy constraints, and human‑in‑the‑loop approvals for high‑risk actions.
• Set up evaluation pipelines and observability for agent reliability, latency, cost, and error rates using LangSmith, OpenAI Evals, or custom telemetry.
• Deploy and operate agent services with Docker, Kubernetes, Terraform, and CI/CD pipelines on AWS, Azure, or GCP, monitoring production behaviour and refining policies.

Required profile

• Bachelor's or master's degree in Computer Science, AI, Data Science, Engineering, or a related field.
• 3+ years of software engineering experience with strong proficiency in Python and/or TypeScript.
• At least 1 year of hands‑on experience building LLM‑powered applications or agentic AI systems in production or near‑production settings.

Required skills

• Python
• TypeScript
• LangChain
• LangGraph
• AutoGen
• n8n
• Make (Integromat)
• Docker
• Kubernetes
• Terraform
• CI/CD pipelines
• AWS, Azure, or GCP
• Vector databases and embedding models
• LangSmith
• OpenAI Evals