3 months ago
Bengaluru, IndiaSenior
Responsibilities
- Design, own, and evolve scalable multi-tenant microservices architectures on Kubernetes across GCP, Azure, and AWS.
- Build platform and data-plane components in Golang and Python for data ingestion, knowledge-base indexing, search, connectivity, workflow automation, and ML operations.
- Own service-to-service communication, including API contracts, service mesh behavior, load balancing, retries, timeouts, and circuit breaking.
- Define architectural tradeoffs involving partitioning, sharding, consistency, caching, and build-versus-buy decisions.
- Establish reliability practices covering SLIs, SLOs, error budgets, capacity planning, autoscaling, and graceful degradation.
- Design and operate observability through metrics, dashboards, tracing, and real-time alerting.
- Drive infrastructure-as-code, Helm, GitOps, and CI/CD platform practices.
- Optimize system performance and cost through profiling, load testing, latency budgets, and cost-per-request analysis.
- Participate in on-call rotations and lead incident response and root-cause analysis.
Requirements
- Bachelor’s degree in Computer Science or a related field.
- 5+ years of experience in Platform, Infrastructure, or Backend Engineering.
- Strong computer science fundamentals, including data structures, algorithms, operating systems, and networking.
- Proficiency in Golang and Python.
- Production experience with Docker, Kubernetes, and microservices architecture.
- Hands-on experience with at least one major cloud provider, with multi-cloud experience strongly preferred.
- Strong database expertise covering optimization, partitioning, sharding, replication, consistency models, NoSQL, graph stores, CAP theorem, and database internals.
- Solid distributed-systems knowledge, including idempotency, backpressure, delivery semantics, and message queues.
- Track record of building platforms from the ground up for use by other engineering teams.
- High-scale systems experience, security and authentication expertise, vector and graph database experience, or open-source infrastructure contributions are bonuses.
Tech Stack
Apache KafkaAWSAzureDockerGoGoogle CloudGoogle Cloud PlatformGrafanagRPCHelmIstioKubernetesNeo4jPrometheusPythonTerraformVault
About Ema
Ema builds an agentic AI platform that delivers AI employees to automate HR, IT, and Finance workflows across existing enterprise systems. It sells to large organizations via enterprise software and implementation services, offering on-prem and air-gapped deployments and 1,000+ prebuilt integrations. Founded in 2023, it has deployments with Wipro and Hitachi.