Middle AI Engineer (AI Agents)

About this role

We’re seeking a Python Developer to join our innovative AI team. This role is focused on building intelligent agents using Microsoft Autogen (or similar tools) and integrating them into AI-driven platforms. You’ll work closely with architects, data engineers, and other developers to create dynamic, adaptive systems that interact with users, data, and tools autonomously. Your work will power solutions in various domains including automation, analytics, and LLM-based product features. Requirements · 4+ years of experience in Python development, including async programming · Hands-on experience with LLM agent frameworks, especially Microsoft Autogen, Langchain, Crew AI, LlamaIndex, etc · Solid knowledge of cloud platforms: Azure, AWS, or GCP (at least one required) · Strong understanding of web development and modern API design (e.g., FastAPI, Flask) · Good experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Redis) · Understanding of Machine Learning basics (e.g., inference pipelines, embeddings, vector stores) · Familiarity with containerized development (Docker) and cloud deployment practices · Solid Git workflow experience, CI/CD pipelines knowledge · English proficiency (Intermediate or higher)

Nice to Have: · Experience building multi-agent systems or working with agent orchestration tools · Exposure to RAG (Retrieval-Augmented Generation) and vector search (e.g., FAISS, Weaviate) · Familiarity with LangChain, LangGraph, LlamaIndex, CrewAI · Hands-on experience with streaming data, event-driven architecture, or message queues (e.g., Kafka, RabbitMQ and its cloud versions like Kinesis and MQ) · Knowledge of observability tools (e.g., Prometheus, Grafana, OpenTelemetry) · Experience with DevOps tools and infrastructure-as-code (Terraform, Helm, etc.)

Responsibilities: · Design and develop intelligent agents using Python and Autogen framework (or similar frameworks) · Collaborate with AI/ML teams to integrate LLMs (e.g., OpenAI, Anthropic, Google, etc.) into multi-agent workflows · Develop and maintain cloud-native applications and services (Azure / AWS / GCP) · Create robust APIs and integrate them with external/internal systems · Implement data ingestion, transformation, and storage logic using SQL, NoSQL, Columnar and Vector DBs · Support system scalability, performance, and maintainability using clean architecture principles · Contribute to agent orchestration logic, tool integrations, and interaction flows · Work closely with the Solutions Architect to align implementation with architecture vision · Write tests, maintain documentation, and participate in code reviews Benefits