Artificial Intelligence Engineer

Responsibilities Collaborate with the team to design and develop high quality Web applications using Python, Flask, Django, and related technologies. Write clean and efficient code, and ensure code maintainability and reusability. Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking, embeddings, indexing, retrieval, reranking, grounding). Build agentic workflows (tool use, planning, reflection/guardrails, structured outputs) using Python-first frameworks. Perform code reviews to ensure code quality and consistency. Conduct testing to ensure application quality and reliability. Create and maintain technical documentation for web applications. Participate in project planning, estimation, and prioritization. Stay up to date with the latest technologies for Python development. Define and run evaluation (retrieval metrics, answer quality, hallucination/grounding checks), and improve system quality iteratively. Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD, and security best practices. Requirements Decent understanding of the software development/testing life cycle. Knowledge of relational databases (e.g. MySQL, PostgreSQL, etc)slanguage skills Experience with version control tools, such as Git. Experience building RAG solutions (hybrid search, reranking, chunking strategies, embeddings, prompt + schema design). Familiar with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex, Semantic Kernel, AutoGen) and tool/function calling patterns. Solid knowledge of vector search concepts and at least one vector DB in production. Strong engineering practices: code reviews, testing, telemetry, secure-by-design, reliability mindset. Preferred Qualifications Master’s Degree in Computer Science, Software Engineering, or related field. 1+ year professional experience in Python web application development with either Flask or Django. Experience in RESTful API development in Python. Understanding of Python web application frameworks such as Flask or Django. Experience with Cloud services, such as AWS. Experience with Vertex AI and GCP fundamentals (IAM, logging/monitoring, Cloud Run/GKE, storage). Knowledge graphs for RAG (entity linking, graph traversal + retrieval fusion). Streaming/messaging (Pub/Sub, Kafka), document pipelines (Document AI), and multilingual retrieval. Experience with evaluation tooling (RAGAS, TruLens, custom eval harnesses), prompt/version management. Frontend integration (basic React/Next.js) or platform enablement (internal developer tooling). BeaconFire is an E-verified company and provides equal employment opportunities (visa sponsorship provided). #J-18808-Ljbffr