This isn’t just another AI job. You’ll be part of a pioneering team pushing the boundaries of what autonomous AI systems can do for Platform Engineering. You’ll have the freedom to innovate, the resources to build at scale, and the support of a colla

This isn’t just another AI job. You’ll be part of a pioneering team pushing the boundaries of what autonomous AI systems can do for Platform Engineering. You’ll have the freedom to innovate, the resources to build at scale, and the support of a collaborative, forward-thinking environment.

We are seeking a skilled d AI Agentic Engineer to join our innovative team. The ideal candidate will have a strong background in artificial intelligence, natural language processing, and software development. This role involves designing, developing, and implementing advanced RAG systems and Agentic AI based solutions that enhance user interaction and content retrieval.

What We’re Looking For

• You eat, sleep, and breathe generative AI — prompt and context engineering, retrieval-augmented generation (RAG), and autonomous agents are your playground.
• You know your way around modern AI agent frameworks like LangChain, LlamaIndex, Semantic Kernel, crewAI, and AutoGen — and you’re excited to push their limits.
• Vector databases like Pinecone, Weaviate, or Chroma? You’re comfortable querying and managing them to power semantic search.
• Full-stack skills? Absolutely. React + TypeScript on the frontend, Node.js or Python microservices on the backend, and REST or gRPC APIs.
• DevOps savvy: Kubernetes, Terraform or AWS CDK, plus monitoring tools like Grafana and Prometheus are in your toolkit.

Key Responsibilities

• Design and Build AI Agents: Create autonomous agents that can reason, plan, act, and collaborate.
• Prompt Engineering: Develop advanced prompts and roles to guide agent behavior.
• Memory & Context Integration: Implement systems for agents to store, recall, and use memory in conversations.
• Tool & API Integration: Enable agents to use external tools and APIs for real-world automation.
• Multi-Step Reasoning: Build agents capable of decomposing tasks, planning, and self-correcting.
• Multi-Agent Systems: Deploy and manage groups of agents that collaborate and delegate.
• Ecosystem Automation: Launch and maintain agentic systems that automate business and technical workflows.
• Collaborate with data scientists and engineers to refine algorithms and improve the performance of AI models.
• Conduct thorough testing and validation of developed systems to ensure accuracy and reliability.
• Stay updated with industry trends and advancements in AI, machine learning, and natural language processing.

The Tech We Love

• AI Agent & Orchestration: LangChain, LangGraph, CrewAU, LlamaIndex, Semantic Kernel, AutoGen
• Protocol: MCP, Agent2Agent
• Vector DBs: Pinecone, Weaviate, Chroma
• Observability & Evaluation: LangSmith, Helicone, PromptLayer, RAGAS
• CI/CD for LLMs: PromptOps, LlamaTest, GitHub Actions with AI evaluation workflows
• Telephony: Twilio Programmable Voice, SIP, VAPI