Senior Infrastructure Engineer
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Before you apply
LocationIndia - Bengaluru
Work modeon-site
Typefull-time
SenioritySenior
Experience5+ yrs
DepartmentEngineering
EquityIncluded
Company size201–500 people
First seenMar 22, 2026 · 7mo ago
Verified live3d ago
May no longer be actively hiring
First seen on the company's careers page 229 days ago64% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
Bachelor's degree in Computer Science or a related field
5+ years of experience in Platform, Infrastructure, or Backend Engineering
Strong CS fundamentals: data structures, algorithms, operating systems, and networking
Proficiency in Golang
Proficiency in Python
Production experience with Docker
Production experience with Kubernetes
Production experience with microservices architecture
Hands-on experience with at least one major cloud provider (GCP, Azure, or AWS)
Strong database expertise: query and read/write-path optimization, partitioning/sharding, replication and consistency models
Practical experience in NoSQL stores
Practical experience in graph stores
Solid grasp of the CAP theorem and database internals
Solid distributed-systems foundation: idempotency, backpressure, delivery semantics
Experience with message queues (Kafka/Pulsar/NATS/PubSub)
Track record of building platforms from the ground up that other engineering teams successfully build on
Experience operating systems at high scale (high QPS, large data volumes)
Multi-cloud experience
Secrets management (Vault)
mTLS
RBAC
OIDC/SAML
Network policy
Experience with vector databases (pgvector/Pinecone/Milvus)
Experience with graph databases (Neo4j/Neptune)
Open-source contributions to infrastructure projects (e.g., Kubernetes operators)
Skills
Golang
Python
Docker
Kubernetes
GCP
Azure
AWS
Terraform
Helm
ArgoCD
Flux
Prometheus
Grafana
OpenTelemetry
gRPC
Protobuf
Istio
Linkerd
HPA
VPA
KEDA
Kafka
Pulsar
NATS
PubSub
NoSQL
pgvector
Pinecone
Milvus
Neo4j
Neptune
Vault
OIDC
SAML
About Ema
Ema builds AI Employees for HR, IT and Finance. Our AI Employees take on the busy work across the employee experience, from recruiting, onboarding and benefits to IT support, invoice processing and payroll, so people can spend their time on work that needs them. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs.
We are backed by industry leading investors including Accel, Naspers/Prosus, Creaegis, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production. We ship real systems that run real business processes at scale.
Who you are
You are an experienced Infrastructure Engineer Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on.
Responsibilities
•
Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC).
•
Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs.
•
Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking.
•
Make and document architectural tradeoffs — partitioning/sharding strategy, consistency models (strong vs. eventual), caching tiers, and build-vs-buy decisions.
•
Define the reliability contract: SLIs/SLOs, error budgets, capacity planning, autoscaling (HPA/VPA/KEDA), and graceful degradation.
•
Design and operate the observability stack — Prometheus, Grafana, OpenTelemetry, distributed tracing, and real-time alerting — for full visibility into system health.
•
Drive DevOps and platform-engineering practices: IaC (Terraform), Helm, GitOps (ArgoCD/Flux), and CI/CD pipelines.
•
Optimize for performance and cost — profiling, load testing, latency budgets, and cost-per-request.
•
Participate in on-call rotations and lead incident response and root-cause analysis.
Qualifications
•
Bachelor’s degree in Computer Science or a related field.
•
5+ years of experience in Platform, Infrastructure, or Backend Engineering.
•
Strong CS fundamentals: 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 (GCP, Azure, or AWS); multi-cloud a strong plus.
•
Strong database expertise: query and read/write-path optimization, partitioning/sharding, replication and consistency models, with practical experience in NoSQL and graph stores. Solid grasp of the CAP theorem and database internals.
•
Solid distributed-systems foundation: idempotency, backpressure, delivery semantics (at-least-once vs. exactly-once), and message queues (Kafka/Pulsar/NATS/PubSub).
•
Track record of building platforms from the ground up that other engineering teams successfully build on.
Bonus
•
Experience operating systems at high scale (high QPS, large data volumes).
•
Depth in auth and security: secrets management (Vault), mTLS, RBAC, OIDC/SAML, network policy.
•
Experience with vector databases (pgvector/Pinecone/Milvus) and graph databases (Neo4j/Neptune).
•
Open-source contributions to infrastructure projects (e.g., Kubernetes operators).
Legal
Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.