AI Engineer Mid-SR

Metova

15d

About The Position

We are looking for an AI Engineer with experience in building and deploying solutions based on intelligent agents, Backend, and cognitive architectures. This role requires knowledge of agent frameworks and protocols (Langchain, Llama, LLMs, NLP, A2A, MCP, etc.) and solid software engineering capabilities to create products with embedded AI. Ideally, someone with knowledge in financial, accounting, payroll, billing, or human resources contexts.

Requirements

4-6 years of experience in artificial intelligence projects, with at least 2+ years in implementing autonomous agents or copilots.
Proven experience using frameworks like LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, or similar.
Practical knowledge of MCP and A2A protocols, tool usage, memory management, and conversation state.
Solid command of Python and experience with FastAPI, asyncio, Pydantic, and asynchronous architectures.
Experience working with vector stores (Chroma, Weaviate, Pinecone) and RAG architectures.
Knowledge in NLP, embeddings, retrieval agents, and reasoning and planning functions.
MLOps knowledge: CI/CD, Docker, Kubernetes, agent monitoring, and automated retraining.
Fluent technical English for reviewing documentation, papers, and collaborating with global teams.

Nice To Haves

Experience in multicloud projects (Azure, AWS, GCP).
Familiarity with event-driven architectures and microservices, as well as RESTful APIs and gRPC.
Experience working with enterprise data in domains such as accounting, finance, payroll, billing, or ERP.
Experience working in development and product teams, as well as high-performance teams/startups.
Practical knowledge of other languages like Golang, Java, or C# (.NET), especially in building high-performance components.
Active participation in agent open-source communities or contributions to emerging frameworks.
Development of innovative products with a focus on AI and data.
Culture of good practices, modern architecture, and collaborative work.

Responsibilities

Experience deploying and programming solutions based on intelligent agents and LLMs, integrating tools like LangChain, LlamaIndex, AutoGen, CrewAI, or equivalent frameworks.
Implement agents that interact with users, APIs, ERP systems, or external platforms (e.g., WhatsApp, accounting systems, CRMs).
Implement MCP (Model Context Protocol) and A2A (Agent-to-Agent) architectures to enable multi-agent coordination and autonomous flows within enterprise environments.
Work in production environments with direct interaction with infrastructure, DevOps, and MLOps teams.
Collaborate closely with product, UX, data, and backend teams for successful delivery of planned functionalities.
Implement with good development practices, validation, and monitoring of agents, including integration tests, prompt version control, and decision traceability.
Stay updated on open-source frameworks and relevant papers in the field of agent frameworks, memory architectures, and multi-agent systems.