AI Engineer - Bengaluru
Description
Overview
Build AI agents and reliable workflows at Live2.ai. An IC4 individual contributor role covering production AI pipelines, evaluation, reproducibility, and ongoing ownership after launch.
Company Details
is building an AI-native Social Content & Campaign Intelligence OS for global consumer brands. It helps brands monitor, audit, analyse, and act on intelligence across social content, influencer campaigns, user-generated content, and commerce. The company works with Fortune 500 global enterprise brands.
Website:
Requirements
Around 3 or more years of software engineering experience, including shipping AI or LLM-backed features to production.
Experience owning those features after launch, including handling failures and production issues.
Hands-on experience building evaluation harnesses and using the results to make release decisions.
Strong general software engineering skills, with an understanding that reliable AI products require substantial systems work.
Ability to reason about and handle failures in components whose outputs can vary for the same input.
Nice to have:
Experience with multimodal pipelines involving vision, audio, or document understanding.
Experience building retrieval systems and evaluating retrieval quality.
Experience handling adversarial input, prompt injection, or abuse resistance.
Experience with fine-tuning, distillation, and the supporting infrastructure.
Experience with workflow orchestration at scale.
Responsibilities
Design and build AI agents and the deterministic workflows they run within.
Work with Backend Engineers on the services supporting these pipelines.
Build and operate multi-step AI pipelines that are idempotent, retryable, observable, and resumable after failure.
Define evaluation datasets, metrics, and release gates before shipping.
Make model behaviour reproducible through versioning, caching, and replay, so historical decisions can be reconstructed.
Protect pipelines against adversarial input and prompt injection through system design, beyond prompt instructions alone.
Measure cost and latency per operation, and treat regressions as bugs.
Work with Site Reliability Engineers to monitor provider latency, failure rates, and cost.
Keep the model layer swappable so changing providers requires a configuration change rather than a rewrite.
Job Details
Bengaluru, in office.
Interview Process
Initial Screening
AI Systems and Evaluation Discussion
Hands-on Engineering Round
Final Discussion
Important Note
ClanX is a recruitment partner, helping hire an AI Engineer.
Skills
As published by recruitee · 17 questions · 6 written answers
Basics
Full name, Email, CV, Phone
Short answers (3)
- Please share your current CTC breakup, including Fixed, Variable, ESOPs, and other components, if any. Please stick to this format: Fixed: 15L, Variable: 3L, ESOPs: 5L with 4-year vesting
- What is your expected annual CTC? (INR)
- Help us with your LinkedIn profile link
Pick from a list (8)
- How many years of experience do you have as an AI Engineer or similar role?
- Are you willing to relocate to Bengaluru?
- What is your notice period? (We are looking for candidates who can join within 30 days)
- Is your notice period negotiable?
- Do you have experience working at a product-based company?
- Are you a citizen of India and currently based in India?
- What does your current or most recent company mainly do?
- What is your current annual CTC range? (INR)
Written answers (6)
- Tell us about the product or services your current or most recent company offers. In 2–3 sentences, explain what it does, who uses it, and share the company/product website.
- Mandatory Loom video: Share a Loom video walking us through one production AI feature or pipeline you personally built. Include its architecture, tech stack, models or providers, the problem it solves, and the scale it handles. Explain your exact contribution, how the workflow handles failures, and what you remained responsible for after launch. You can anonymise confidential details.
- Describe an evaluation harness you personally built for an AI feature. What did your dataset test, which metrics and release thresholds did you use, and how did the results influence an actual release decision? Include one failure the evaluation caught and what you changed.
- After exploring Live2.ai (https://live2.ai/), explain in your own words what the company does, who its customers are, and the problem it solves. Describe one AI workflow you think could support the product, where it might fail, and how your past experience would help you build it reliably. Your company research and understanding of the product carry significant weight in our evaluation.
- Why do you want to leave your current role?
- Where did you find this job opportunity? (e.g., LinkedIn, Twitter, WhatsApp, etc). If someone referred you, please mention their name and contact number so we can thank them. (Write NA if not applicable).
