- Company Name
- AODocs
- Job Title
- Staff Engineer - AI
- Job Description
-
Job title: Staff Engineer – AI
Role Summary: Lead the design, development, and deployment of AI‑driven features within a cloud‑native content services platform. Own end‑to‑end AI components—agentic RAG pipelines, semantic extraction, hybrid search, and LLM integration—while ensuring scalability, reliability, and governance across enterprise document corpora.
Expectations:
- Deliver high‑impact, production‑grade AI solutions at scale.
- Champion technical excellence, set engineering standards, and mentor teammates.
- Collaborate cross‑functionally with product, frontend, and infrastructure squads.
- Own feature specifications, architecture, and release pipelines.
Key Responsibilities:
- Architect and implement agentic Retrieval‑Augmented Generation (RAG) pipelines, including query planning, re‑ranking, and multi‑hop reasoning.
- Develop intelligent document processing services (OCR, layout analysis, entity extraction, classification) at large scale.
- Build a unified search layer that merges semantic vector search with traditional full‑text retrieval, ensuring latency and governance compliance.
- Design and evolve microservices with clean hexagonal boundaries for cloud‑agnostic operation.
- Drive the integration of large language models (LLMs) into the existing document platform architecture.
- Maintain high performance, reliability, and system quality across all deployments.
- Write and enforce high‑standard API contracts and documentation.
Required Skills:
- Strong proficiency in Java and/or Python; experience with Go and JavaScript acceptable.
- Deep understanding of cloud services (Google Cloud Platform, serverless compute, Pub/Sub, Cloud Run, Cloud Functions, Firebase).
- Expertise in AI/ML pipelines: RAG, LLMs (ChatGPT, GPT‑4, LLaMA, etc.), semantic embedding, dense/sparse retrieval.
- Experience with OCR, document layout analysis, and entity extraction frameworks.
- Knowledge of microservices architecture, hexagonal design, and cloud‑agnostic deployment patterns.
- Ability to perform performance tuning, reliability testing, and observability best practices.
- Strong communication skills for cross‑functional collaboration and technical mentorship.
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field.
- Certifications in cloud platforms (e.g., Google Professional Cloud Architect) and AI/ML engineering preferred.