Member of Technical Staff – Applied AI Engineering

Location: On-site in Bengaluru, India; work hours aligned with US timings

Company

hirify.global builds infrastructure that enables AI agents to communicate with workplace tools such as GitHub, Gmail, Notion, and Salesforce.

What you will do

• Build agentic workflows for support intake, classification, context gathering, diagnosis, response drafting, remediation, verification, and follow-up.
• Develop tool-using agents that inspect runs, logs, authentication state, configuration, and provider behavior, then execute bounded recovery actions.
• Create evaluation suites for diagnostic correctness, resolution quality, safe escalation, customer communication, and end-to-end completion.
• Design human-in-the-loop systems with explicit ownership, permissions, approvals, handoffs, uncertainty, and failure states.
• Own complex customer issues end to end by reproducing failures, identifying root causes, shipping fixes, and verifying resolutions.
• Turn recurring customer problems into reliable workflows, product improvements, observability, memory, and feedback loops.

Requirements

• 2–4 years of professional software engineering experience.
• Production experience with language models, tool calling, retrieval, structured outputs, multi-step workflows, or agent memory.
• Experience shipping and operating backend, platform, or integration software.
• Ability to debug SDKs, HTTP, OAuth, webhooks, queues, data stores, logs, and third-party APIs.
• Ability to design support systems around states, tools, permissions, verification, escalation, and human fallback.
• Strong communication with technical customers and cross-functional partners under uncertainty.

Nice to have

• Production experience with TypeScript or Python.
• Experience building AI agents, copilots, workflow automation, or evaluation infrastructure.
• Experience with developer platforms, API products, support engineering, SRE, or incident response.
• Familiarity with OAuth 2.0, webhooks, rate limits, Postgres, queues, cloud observability, Plain, Zendesk, Intercom, or Salesforce.
• Public technical writing, open-source contributions, or strong debugging documentation.

Culture & Benefits

• Customer-facing applied AI engineering rather than traditional support work.
• Direct collaboration with Support, FDE, Product, Engineering, and technical users.
• Daily use of frontier models, coding agents, and internal AI tools.
• Emphasis on customer outcomes, reliable production systems, safe automation, and preventing recurring failures.