AI Platform Engineer

We are developing an innovative AI-powered knowledge platform that integrates data from diverse sources such as code repositories, documentation, and project management tools including Git, Jira, Azure DevOps, Quickbase, Office documents, and meeting transcripts. This platform enables AI to provide precise, source-verified answers for requirements gathering, codebase analysis, and AI-assisted software development. As a key contributor, you will take full ownership of the platform’s lifecycle, including the ingestion pipeline, multi-source retrieval-augmented generation (RAG), and the complete full-stack application.

Key Responsibilities
- Develop a unified, incremental ingestion pipeline leveraging APIs, webhooks, and connectors. This includes tasks such as parsing, normalization, deduplication, and metadata extraction.
- Design and implement multi-source RAG workflows encompassing chunking, embeddings, indexing, hybrid retrieval, reranking, and context assembly.
- Enable AI to comprehend large codebases by analyzing structure, symbols, dependencies, and APIs, and automate the generation of architecture documentation.
- Build backend services using Python (FastAPI) and frontend components with JavaScript/Node.js for search, data intake, and visualization functionalities.
- Ensure permission-aware data retrieval, maintain provenance, and support auditability throughout the entire data pipeline.
- Apply test-driven development (TDD), automated testing—including retrieval-quality tests—and manage continuous integration and continuous deployment (CI/CD) pipelines using Azure DevOps.

Required Qualifications
- Minimum of 5 years of strong experience in Python and backend development.
- Proven hands-on experience in building large language model (LLM) applications and RAG pipelines.
- Expertise in data ingestion, RESTful APIs, webhooks, and integrating third-party services.
- Full-stack development skills with proficiency in JavaScript and Node.js.
- Familiarity with Azure DevOps, Git workflows, and CI/CD best practices.
- Solid understanding of authentication, authorization, and secure data access principles.

Preferred Qualifications and Benefits
- Experience with FastAPI, Pydantic, LangChain, or LlamaIndex frameworks.
- Knowledge of vector databases such as Pinecone, ChromaDB, or FAISS, including retrieval evaluation techniques.
- Background in abstract syntax tree (AST) parsing, symbol indexing, dependency graphs, and knowledge graph construction.
- Competence with Docker, cloud infrastructure, and observability tools.
- Experience integrating Jira and Quickbase, along with implementing AI governance controls.

Joining this team offers the opportunity to build a high-impact AI platform from the ground up. You will collaborate closely with architects and product stakeholders in an iterative, security-first environment, contributing to cutting-edge technology that drives AI-assisted software development forward.