Generative Ai Engineer

Location : Remote (Applications open worldwide)Compensation : $20,

• ,000 / year (based on experience and scope of ownership)Skills : Semantic Search, Vector Databases, Prompt Engineering, GenAI Frameworks, React Agents, Graph Agents, Document Parsing, Python, Scalable APIsAbout AnswerThisAnswerThis is an AI-powered research platform built to eliminate the most time-consuming part of academic research : the literature review.

We serve researchers globally, from PhD students to academic professionals, helping them go from query to a comprehensive, cited review in minutes.Our system understands how papers connect, ranks relevance, summarizes insights, and maps citations.

This removes weeks of manual work.

But that is just the beginning.

We are building a vertically integrated AI research suite that streamlines every stage of academic discovery.If you want to design algorithms that directly accelerate science in medicine, AI, climate, and more, this is the place to do it.The RoleWe are hiring an AI Engineer to lead the development of the core intelligence behind AnswerThis.

This role requires deep expertise in information retrieval, scalable backend systems, and generative AI.You will : Build and optimize semantic search pipelines, graph-based retrieval, and agentic systems.Design and deploy scalable APIs and services capable of serving hundreds of concurrent requests.Architect, implement, and productionize vector databases and embedding-based retrieval systems.Work on GenAI integrations including react agents, graph agents, prompt engineering, and LLM orchestration.Set up full-stack search engines from scratch that can handle real-world academic workloads.Contribute directly to the infrastructure that makes cutting-edge science more efficient.This is a hands-on role with real ownership.

You will move fast, experiment, and ship production systems that impact thousands of researchers worldwide.RequirementsStrong background in semantic search, vector databases, LLM frameworks, agent-based systems, and document retrieval.Skilled in Python for backend development with the ability to build scalable APIs and services.Past experience deploying systems at scale, including search engines, retrieval pipelines, or embedding models.Ability to design infrastructure that serves hundreds of concurrent requests.Experience setting up and hosting APIs with public access while balancing speed, cost, and reliability.A research-driven and pragmatic mindset with a focus on measurable outcomes.Compensation$20,

This is a full-time role with significant responsibility and long-term upside.How to ApplySend the following to