AI Engineer - Bengaluru
Clanx · Bengaluru, Karnātaka, India · Onsite
Strong hiring record · median 14 days open
Hiring signal
Actively hiring
Posted yesterday · still listed on the employer's own board · How we score
All reasons
In its favour
- Posted yesterday
- Still listed on the employer's own board
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
Live2.ai 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
https://live2.ai/
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 Live2.ai hire an AI Engineer.
Skills
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