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About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. 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, 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 Platform 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). Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics. 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.