Job Description & Details
This is a hands-on backend and AI engineering role focused on building the core frameworks that drive autonomous workflows for Fortune 500 clients. If you enjoy moving past simple API wrappers and want to build robust multi-agent systems and production-grade RAG pipelines, this is worth a serious look.
What You'll Actually Be Doing
You will spend your days architecting and deploying agentic workflow frameworks that allow systems to execute complex business tasks autonomously. Expect to spend a lot of time writing clean backend code to handle API integrations, optimizing retrieval-augmented generation pipelines, and ensuring your LLM orchestration layers don't choke under production loads. You'll work closely with product teams to translate abstract automation concepts into reliable, highly available distributed backend services.
The Core Tech Stack
You need a strong foundation in Python and deep familiarity with modern Generative AI tooling like LangChain, OpenAI APIs, and Claude. Beyond just calling endpoints, they need someone who truly understands how to construct efficient RAG architectures, handle asynchronous processing, and build robust evaluation pipelines. If you haven't dealt with the nuances of token management, state persistence in multi-agent systems, and prompt engineering at scale, you'll find this uphill.
Interview Expectations
Expect the engineering team to grill you on how you handle failure states and hallucinations when integrating LLMs into automated execution loops. They will likely ask you to design a fault-tolerant RAG system and explain how you would debug a multi-agent deadlock. The interviewer isn't just looking for textbook definitions; they want to see your war stories on how you've handled latency, rate limits, and data leakage in production AI systems.
Application Advice
Skip the generic objectives and tailor your resume to scream 'Systems + AI.' Highlight any production experience you have with LangChain, vector databases, and heavy backend API integrations rather than just weekend hobby projects. Make sure to explicitly mention terms like RAG, agentic workflows, LLM orchestration, and high-availability backend architecture so your resume sails past the recruiter's ATS.