Staff Software Engineer

Software Engineer — Bengaluru, India

About Auxia

Auxia is an agentic AI platform that helps enterprises deliver personalized 1:1 customer journeys. Our Decision Agent determines the optimal message, timing, channel, and incentive for each individual user — processing 3B+ events/day, 25K+ queries/second, and 1B+ decisions/day at sub-100ms latency.

We serve global enterprises including Atlassian, The Guardian, Docomo, Comcast, Mercari, and MUFG Bank and many more across email, push, in-app, and messaging channels. Backed by $23.5M from VMG Technology Partners, Stage 2 Capital, and MUFG Innovation Partners.

——————————————————————————————————————————————

The Hard Problems

Auxia isn't a typical SaaS platform. Here's what makes the engineering genuinely interesting:

-
Multi-tenant ML serving at scale. A single shared platform serves 20+ enterprise customers, each with millions of users, hundreds of treatments, and unique business constraints — all at sub-100ms p99. Every architectural decision has to balance isolation, performance, and cost across customers.

-
Real-time decisioning under uncertainty. Our Decision Agent picks the best action for each user from hundreds of options using bandits and other ML models, learning continuously from live interactions. Cold-start, exploration-exploitation tradeoffs, and feedback loops are daily problems.

-
Enterprise data integration. Every customer brings different data formats, volumes, schemas, and infrastructure (Snowflake, BigQuery, S3, CDPs). Onboarding a new customer's data pipeline needs to be fast and reliable — we're building toward fully automated ingestion.

-
Agentic AI systems. Our Analyst Agent autonomously builds data semantic layers, constructs and executes efficient queries, and runs complex analyses and generates insights for enterprise marketers, and generates insights for enterprise marketers. Building reliable, observable AI agents that interact with real production data is a frontier problem.

What You'll Work On?

Depending on your interests and strengths, you'll work across some combination of:

-
Platform Infrastructure — Kubernetes orchestration on GCP, service mesh, deployment automation, observability (metrics, tracing, alerting), cost optimization across a multi-region platform.

-
Data Systems — High-throughput data processing pipelines (Apache Beam/Dataflow, Pub/Sub, Airflow), BigTable and BigQuery at terabyte scale, real-time feature stores, data warehouse and reporting infrastructure.