Junior AI / Python Engineering

Position Overview

We are seeking an enthusiastic Junior Python Engineer with a passion for Artificial Intelligence, streaming data, and edge devices to join our growing engineering team. In this role, you will help design, build, and deploy intelligent Python services that process real-time data feeds and leverage cutting-edge AI models.

You will work alongside senior software engineers and data scientists to build applications that connect physical data sources (sensors, IoT devices) with local and cloud-based AI tools. This position is ideal for a junior developer eager to build practical, production-ready AI applications in a high-throughput environment.

 Key Responsibilities

 Write clean, modular, and maintainable Python code for data ingestion pipelines, microservices, and API endpoints.

 Assist in building and optimizing retrieval-augmented generation (RAG) pipelines and query engines to search and analyze unstructured data using AI models.

 Help build and maintain backend consumers that process real-time telemetry, time-series, and sensor data feeds.

 Assist with testing, benchmarking, and integrating open-source Large Language Models (LLMs) running locally or on-premise.

 Write unit tests and conduct data validation checks to ensure the reliability and accuracy of AI outputs and streaming data inputs.

 Participate in code reviews, daily standups, and contribute to system architecture documentation and API specs.

Technical Capabilities & Requirements

·        At least 1 years of practical experience in Python development.

·        Strong foundation in Python syntax, standard libraries, object-oriented programming (OOP), data structures, and asynchronous concepts (asyncio).

·        Experience building or consuming REST APIs using frameworks like FastAPI or Flask.

·        Experience to work with machine learning concepts, NLP, or modern AI tools (e.g., NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, or LLM APIs) in real projects.

·        Familiarity with relational databases (e.g., PostgreSQL, SQLite) and basic SQL query writing.

·        Proficiency with Git (branching, pull requests, commit history).

·        Eagerness to learn new frameworks quickly and troubleshoot complex data or AI-related bugs logically.

Nice-to-Haves (Bonus)

 Experience running local models or LLM runners using Ollama or similar local deployment tools.

 Exposure to indexing and retrieval frameworks like LlamaIndex or vector databases (e.g., Chroma, Qdrant, PGVector).

 Basic understanding or project experience with Apache Kafka or other event-driven streaming architectures (e.g., RabbitMQ).

 Familiarity with processing sensor telemetry, time-series data, or IoT protocols (e.g., MQTT, Modbus, HTTP webhooks).

 Basic exposure to Docker for creating local development environments.