Software Developer (AI)

Job Description: This is NOT a traditional full stack or backend role anymore. Built end-to-end AI / agentic applications Understand what goes into an LLM, what comes out, and how to use it Can productionize AI systems (not just prototype) 2. Ability to Turn LLM Output into Action Key expectation: “Don’t just call an LLM - do something meaningful with the output” Candidates should demonstrate: Structured output handling Workflow orchestration Turning AI responses into usable application features 3. Productionization > Prototyping This is where candidates are currently falling short. Ross is heavily focused on: How AI apps are moved into production environments Understanding of: CI/CD in enterprise environments Deployment workflows Reliability & operational considerations They don’t have to build CI/CD pipelines themselves But must understand how production systems work at a high level 4. Deep Understanding of Agentic Systems Candidates must be able to confidently discuss: Memory management in agentic applications How agents: Maintain context Store/retrieve information Execute multi-step workflows

Do you have experience in Production systems?