AI Automation Engineer

Job Description

We are seeking a skilled Python engineer with 2 to 5 years of experience to join our team as an AI/Automation Engineer. In this role, you will develop AI-powered features and automated workflows, working across backend APIs, large language model (LLM) integration, retrieval systems, and workflow automation. You will be responsible for designing and delivering end-to-end AI solutions that transform raw data through models into reliable outputs that support business needs.

Key Responsibilities

– Develop and maintain Python backend services and APIs to support AI features.
– Integrate LLMs into product functionalities, including prompting, structured output, and tool calling.
– Design and optimize Retrieval-Augmented Generation (RAG) pipelines involving chunking, embeddings, vector search, and retrieval quality.
– Build automated workflows connecting systems, APIs, and AI components.
– Work with both vector and relational databases to ensure efficient data handling.
– Measure and enhance the accuracy, latency, and cost-effectiveness of AI features.
– Write comprehensive tests and documentation alongside code development to ensure maintainability and quality.

Required Qualifications

– 2 to 5 years of professional experience in Python software development.
– Proficiency with web frameworks such as FastAPI, Flask, or Django, including REST API design, validation, and asynchronous programming.
– Hands-on experience integrating LLM APIs into production applications.
– Solid understanding of RAG techniques, including embeddings, chunking, and retrieval.
– Strong knowledge of SQL and relational database design.
– Familiarity with Git, code review processes, and testing best practices.
– Clear and effective written communication skills.

Preferred Qualifications and Benefits

Automation Expertise

– Experience with automation tools like n8n, Make, Zapier, Airflow, or Temporal for building multi-step workflows.
– Skilled in API integration and webhook-driven automation.
– Knowledge of scheduled jobs, queues, and background processing.
– Ability to automate internal and operational processes end to end.

AI and Advanced Technologies

– Familiarity with agentic RAG concepts such as query planning, iterative retrieval, and self-correction.
– Experience with AI agents involving tool calling, multi-step reasoning, and implementing guardrails.
– Working knowledge of vector databases such as Qdrant, pgvector, Chroma, Pinecone, or Weaviate.
– Understanding of hybrid search and reranking techniques.
– Expertise in prompt and context engineering.
– Ability to evaluate AI outputs for accuracy, grounding, and hallucination control.
– Experience running open-source models locally using tools like Ollama, vLLM, or Hugging Face.
– Familiarity with frameworks such as LangChain, LlamaIndex, or similar.
– Knowledge of Model Context Protocol (MCP) and current agent tooling.

Additional Skills

– Basic experience with Docker and Linux environments.
– Exposure to document processing technologies including OCR, PDF parsing, and vision models.
– Frontend development familiarity, particularly with React and TypeScript.
– Experience with cloud platforms such as AWS, GCP, or Azure.
– Contributions to open-source projects or personal AI-related initiatives.

We value curiosity and self-direction, as the AI and automation field evolves rapidly. We seek candidates who stay updated out of genuine interest rather than obligation. Honesty about knowledge gaps and a data-driven approach to feature validation are essential. We want someone who cares deeply about whether a feature truly works, beyond just how well it demos.