Senior AI Engineer - Graph Systems & Agentic AI - Zenara Health at 2070Health

, , India -

Full Time

Start Date

Immediate

Expiry Date

03 Mar, 26

Salary

0.0

Posted On

03 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Graph Databases, LLM Integration, API Integration, ETL, Data Ingestion, Rendering Algorithms, Provenance Tracking, Temporal Decay, Communication Skills

Industry

Venture Capital and Private Equity Principals

Description

Location: India (Remote) Reports to: Founder/CEO ABOUT THE ROLE: We're building a novel AI memory architecture that will power the next generation of deeply grounded AI agents. This is not a chatbot or a simple RAG pipeline — it's foundational infrastructure for AI that truly understands humans and their work. As our first AI engineer, you'll architect and build: - A graph database storing entities, relationships, and events from multiple sources - Ingestion pipelines from meeting transcripts, emails, notes, and ambient capture - A rendering engine that produces LLM-optimized canonical views - An agentic AI layer with tools for retrieval and graph queries You'll work directly with the founder, a physician-technologist building AI for healthcare and beyond. WHAT YOU'LL DO: - Design and implement graph database schemas (Neo4j, Kuzu, or similar) - Build data ingestion pipelines from APIs (Fireflies, HubSpot, Evernote, etc.) - Develop LLM integration layers with function calling and tool use - Create rendering algorithms for context-window-optimized canonical views - Implement provenance tracking and temporal decay mechanisms - Collaborate on architectural decisions and trade-offs MUST HAVE: 5+ years software engineering experience Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field from one of India’s top institutes (e.g., IITs, BITS, IISc). Expert-level Python (async, FastAPI, data pipelines) Strong experience with graph databases (Neo4j, Memgraph, Kuzu, or similar) Experience integrating LLMs into production systems Familiarity with RAG, embeddings, and vector databases Strong API integration and ETL experience Excellent communication skills NICE TO HAVE: Healthcare domain experience (HIPAA, FHIR) Experience with ambient capture / transcription systems Contributions to open-source AI/graph projects Startup or early-stage experience Competitive compensation (depending on experience) Equity participation Direct collaboration with founder Opportunity to build foundational AI infrastructure Remote-first culture

Responsibilities

As a Senior AI Engineer, you will design and implement a graph database and build data ingestion pipelines. You will also develop LLM integration layers and create rendering algorithms for optimized views.