Applied AI Engineer

Company: Weekday AI

Role summary

Applied AI Engineer is a full-time role at Weekday AI in Bengaluru, Karnataka, India (on-site). Posted 2026-09-09. Experience level: 2-5.

Job title
Applied AI Engineer
Company
Weekday AI
Location
Bengaluru, Karnataka, India
Work arrangement
on-site
Employment type
full-time
Category
AI & Machine Learning
Experience level
2-5
Date posted
2026-09-09

If you're excited about building the future with cutting-edge artificial intelligence, this full-time Applied AI Engineer role could be a fantastic fit! You'll have the chance to dive deep into AI development and contribute to innovative projects.

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.

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.

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