Applied AI Engineer

Weekday AI; Bengaluru; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Weekday AI in Bengaluru, India is seeking an engineer to automate post-sales workflows by building internal tools and AI-powered agents. You will ship integrations across CRM, support, billing, and data platforms, partnering with CS and onboarding teams for high-leverage impact.

You’ll design LLM-powered features for document retrieval, summarization, drafting, and classification, with a focus on accuracy and guardrails, shipping end-to-end automations that save time and improve outcomes.

Qualifications

• Minimum 2 years of experience in AI/automation.
• Experience shipping internal tools and automations.
• Familiarity with APIs and integration platforms.

Responsibilities

• 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.

Skills

AI development

Automation

LLM integration

API integration

Data analysis

Job description

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.