--- title: 'Platform Engineer at Ema' canonical: 'https://feeny.ai/job/platform-engineer-ema-bengaluru-4wpanhmc2xj5' type: 'job' last_seen: '2026-10-14' --- # Platform Engineer at Ema - **Company:** Ema - **Location:** Bengaluru, India - **Employment:** full-time - **Posted:** 2026-06-19 - **Last confirmed live:** 2026-10-14 - **Apply:** https://jobs.ashbyhq.com/ema/748c829c-cb1d-48cf-90da-780593e89bea ## Job description ## 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 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. ## About Ema ## Company Overview - **One-liner**: Ema provides a universal agentic control plane that enables enterprises to build, deploy, and scale autonomous AI agents to automate complex workflows across every business function. - **Entity Type**: Private (Series A) - **Headquarters**: San Francisco, California, United States - **Founded**: March 2023 - **Founders**: Surojit Chatterjee (Co-Founder & CEO), Souvik Sen (Co-Founder & CTO) ## Core Business - **Primary industry**: Enterprise AI Software / Generative AI / Agentic AI - **Target customers**: Large enterprises across healthcare, financial services, legal, and technology sectors (B2B, Enterprise) - **Mission or purpose statement**: To give business and IT leaders one place to build, deploy, and scale AI Agents across every function—HR, Finance, Sales, Customer Support, Legal, and beyond. The company believes the future of work is "humans multiplied by AI Employees," not humans replaced by AI. ## Products & Services - **Ema Universal Agentic Control Plane**: A platform for building, deploying, and scaling AI Agents across all enterprise functions. - **EmaFusion™**: A patented AI fusion layer that blends 100+ LLMs to optimize for accuracy, cost, and latency on every query, without vendor lock-in. - **GWE™ (Generative Workflow Engine)**: The orchestration core that breaks complex enterprise workflows into multi-agent steps, with built-in human-in-the-loop, audit trails, and async operations. - **Enterprise Context Graph**: Deep, permissioned memory across an organization's data, systems, and processes so every AI Employee knows the business from Day One. ## Market Standing - **Valuation**: Not publicly disclosed - **Total Funding**: $75 million (across multiple rounds) - **Seed Round** (March 2024): $25M led by Prosus Ventures and S32 - **Series A** (July 2024): $36M led by Accel and S32 - **Additional Series A** (March 2026): $14M from 9 investors - **Notable Investors/Partners**: Accel, S32 (Section 32), Prosus Ventures, Hitachi Ventures, KPMG (strategic investment) - **Growth Signals**: - Employee headcount grew 89.2% year-over-year to 155 people. - Operates in 6 countries (US, India, UK, Canada, UAE, Germany). - Trusted by global enterprises across highly regulated industries. - Holds certifications including ISO 42001 (world's first AI management standard), SOC 2 Type II, ISO 27001, and HIPAA. - Supports on-premises and air-gapped deployment, a significant differentiator for security-conscious enterprises. ## Competitive Advantages - **EmaFusion™ Technology**: A proprietary multi-model approach that blends over 100 LLMs, optimizing for accuracy, cost, and latency while avoiding vendor lock-in. - **Enterprise-Grade Security & Compliance**: One of the few agentic AI platforms that supports on-premises and air-gapped deployment, with certifications like ISO 42001, SOC 2 Type II, ISO 27001, and HIPAA. - **Deep Enterprise Integration**: Pre-integrated with 200+ enterprise systems, with a permissioned "Enterprise Context Graph" that provides deep, institutional memory. - **Strong Strategic Backing**: Backed by top-tier VCs (Accel, S32) and a strategic investment from KPMG, signaling strong enterprise credibility. ## Strategic Focus - **Product Expansion**: Continuing to build out the agentic AI platform to cover more enterprise functions and workflows. - **Enterprise Adoption**: Deepening relationships with large, regulated enterprises (healthcare, financial services, legal). - **Global Scale**: Expanding operations across key markets (US, India, UK, Canada, UAE, Germany) to support a global customer base. - **Trust & Compliance**: Maintaining and expanding certifications (ISO, SOC 2, HIPAA) to meet the highest enterprise security standards. ## Why Work Here - **Culture**: Ema describes itself as an "AI-first" company that hires "fewer people with a hunger and growth mindset" and augments the human workforce with AI employees. Core values include being innovative, trusted, relentlessly driven, and bold. - **Engineering Philosophy**: The company has a published "Engineering Manifesto" and emphasizes hiring "builders and creators." They believe a "10x team is better than a 10x individual" and operate with a "no wait, no boundaries" approach. - **Work Environment**: "Everyone builds" is a key principle—employees are expected to write software, create original content, and build new processes regardless of their formal role. - **Remote/Hybrid Policy**: Not explicitly stated, but offices are located in the SF Bay Area (US), India, UK, and Canada, suggesting a global, likely hybrid-friendly setup. - **Talent Pool**: The company attracts talent from top tech companies (Google, Meta, Amazon, Coinbase, Databricks) and top universities (IIT Delhi), indicating a high-caliber peer group. - **Open Roles (as of mid-2026)**: 32 active job postings, including roles in ML Engineering, Backend Engineering, DevOps, Product Management, Security & Compliance, and Marketing. ## Sources 1. [ema.ai/careers](https://www.ema.ai/careers) 2. [jobs.ashbyhq.com/ema](https://jobs.ashbyhq.com/ema) 3. [Crunchbase - Ema](https://www.crunchbase.com/organization/ema-8724) 4. [LinkedIn - Ema](https://www.linkedin.com/company/ema-unlimited) 5. [Tracxn - Ema](https://tracxn.com/d/companies/ema/__ksb3jUKrtsxUjw6V-pJ_Daac843jAQUG62LqeRWEGJ0) ## Other roles at Ema - [Devops Engineer, US](https://feeny.ai/job/devops-engineer-us-ema-mountain-view-6xs6vam1xfxy) — Mountain View, CA - [IT Engineer](https://feeny.ai/job/it-engineer-ema-san-francisco-1g6631qr9fjg) — San Francisco, CA - [AI Resident UK/EMEA](https://feeny.ai/job/ai-resident-uk-emea-ema-united-kingdom-499aq5tctc5a) — United Kingdom - [Sales Development Representative](https://feeny.ai/job/sales-development-representative-ema-united-states-5xq9tbb76n09) — United States - [Software Engineer, Full-Stack](https://feeny.ai/job/software-engineer-full-stack-ema-san-francisco-zetv3r0q2r6n) — San Francisco, CA - [Software Engineer, Machine Learning](https://feeny.ai/job/software-engineer-machine-learning-ema-vancouver-chp4xdz8xx6m) — Vancouver, Canada - [Field Marketing Manager, EMEA](https://feeny.ai/job/field-marketing-manager-emea-ema-united-kingdom-ftj8q0ayw809) — United Kingdom - [Software Engineer, Full-Stack](https://feeny.ai/job/software-engineer-full-stack-ema-vancouver-ktj8sbzdgr3w) — Vancouver, Canada - [Partner Manager - UK](https://feeny.ai/job/partner-manager-uk-ema-united-kingdom-wjefgt06nw9f) — United Kingdom - [Product Manager, UK](https://feeny.ai/job/product-manager-uk-ema-united-kingdom-c5rn0ymc65x6) — United Kingdom