Proven Professional Experience: A minimum of 3 years in backend engineering, with a strong portfolio of building scalable, production-grade systems using robust Python skills. This includes deep, hands-on experience with database management.
Deep expertise in FastAPI and a strong appreciation for its asynchronous capabilities. Also utilizing RUST programming language is highly valuable
Mastery of Pydantic for creating strict, type-safe data models that enforce architectural clarity.
Experince in any of common agentic frameworks such as langGraph, Pydantic-AI, Google ADK, Agno or any similar framework
Strong command of PostgreSQL, including advanced schema design, query optimization, and indexing strategies.
Production-level experience with Docker, with a proven ability to write clean, multi-stage Dockerfiles and manage containerized applications.
A profound passion for AI and a demonstrable interest in agentic systems. You have likely experimented with frameworks like LangChain, LlamaIndex, or AutoGen, or you possess a strong desire to build such systems from fundamental principles.
A systems-thinking approach. You can visualize how disparate components—LLMs, databases, APIs, and tools—integrate to form a single, intelligent entity.
Insatiable Curiosity: You are constantly learning and exploring the bleeding edge of AI and software engineering.
Ownership Mentality: You don't just write code; you take ownership of the systems you build and are accountable for their performance and reliability.
Collaborative Spirit: You thrive in a team environment, sharing knowledge and elevating those around you.
Experience with vector databases (e.g., Pinecone, Chroma, Weaviate).
Knowledge of cloud platforms (AWS, GCP, Azure) and infrastructure-as-code (Terraform).
Familiarity with CI/CD pipelines (e.g., GitHub Actions, GitLab CI).
Experience with message queues (e.g., RabbitMQ, Kafka) for asynchronous task processing.
