AI Engineer - Bangalore

CLANX; Bengaluru; On-site; INR 2,400,000 - 4,800,000; Full time

Job summary

Live2.ai in Bengaluru is seeking an IC4 software engineer to design and operate AI agents and reliable, multi-step pipelines that run deterministically after deployment.

You will work with backend teams to build supported services, define release gates and evaluation datasets, and ensure reproducibility through versioning and caching. The role focuses on resilience, cost, latency, and safe handling of adversarial inputs.

Qualifications

• 3-5 years of software engineering experience including shipping AI or LLM-backed features to production.
• Ownership after launch including handling failures and production issues.
• Hands-on experience building evaluation harnesses and using results for release decisions.
• Strong general software engineering skills with focus on reliable AI products.
• Ability to reason about and handle failures in components whose outputs can vary for the same input.

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 to reconstruct historical decisions.
• Protect pipelines against adversarial input and prompt injection through system design.
• 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.

Skills

Production AI

Ownership

Evaluation harnesses

Reliability

Failure handling

Job 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

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

• 3-5 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