Applied AI Engineer
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What you'll do
- Build AI applications and agents that automate post-sales workflows — onboarding health checks, usage/adoption reviews, ticket triage, knowledge-base answering, and SOAP/billing lookups.
- Design and ship internal automations across the post-sales stack (support, CRM, billing, data warehouse) so manual steps disappear.
- Develop LLM-powered features: retrieval over product docs and knowledge bases, summarization, drafting, and classification — with an eye on accuracy and guardrails.
- Integrate systems via APIs and connectors (Slack, email, Jira, analytics/BI, internal Spry services) into reliable end-to-end workflows.
- Instrument everything: define success metrics, monitor quality, and iterate based on real usage.
- Partner directly with CS, onboarding, and support leads to find the highest-leverage problems and prototype fast.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
This role is for one of Weekday’s clients
Min Experience: 2+ years
Location: Bengaluru, Karnataka, India
JobType: full-time
You'll be embedded with the post-sales team as the engineer who turns their most painful, repetitive workflows into automations and AI applications. This is a builder role: you'll ship internal tools, LLM-powered agents, and integrations that make onboarding, support, and account management faster and more accurate. You'll sit close to the people using your work, iterate quickly, and measure impact in hours saved and customer outcomes.
Requirements
What You'll Do
- Build AI applications and agents that automate post-sales workflows — onboarding health checks, usage/adoption reviews, ticket triage, knowledge-base answering, and SOAP/billing lookups.
- Design and ship internal automations across the post-sales stack (support, CRM, billing, data warehouse) so manual steps disappear.
- Develop LLM-powered features: retrieval over product docs and knowledge bases, summarization, drafting, and classification — with an eye on accuracy and guardrails.
- Integrate systems via APIs and connectors (Slack, email, Jira, analytics/BI, internal Spry services) into reliable end-to-end workflows.
- Instrument everything: define success metrics, monitor quality, and iterate based on real usage.
- Partner directly with CS, onboarding, and support leads to find the highest-leverage problems and prototype fast.
Company
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