PRINCIPAL ARCHITECT

Who We Are

Ema is building the next generation AI technology to empower every employee in the enterprise to be their most creative and productive. Our proprietary tech allows enterprises to delegate most repetitive tasks to Ema, the AI Employee.

We are founded by ex-Google, Coinbase, and Okta executives and serial entrepreneurs. Weve raised capital from notable investors including Accel Partners, Naspers, and Section32, along with prominent Silicon Valley angels such as Sheryl Sandberg (Facebook/Google), Jerry Yang (Yahoo), Dustin Moskovitz (Facebook/Asana), David Baszucki (Roblox CEO), and Gokul Rajaram (DoorDash, Square, Google).

Our team comprises engineers from Google, Microsoft Research, Facebook, Square/Block, and Coinbase — with most hailing from top-tier institutions like Stanford, MIT, UC Berkeley, CMU, and IIT.

THE ROLE

As a Principle Architect at Ema, you will build and lead a high-performance engineering organization — setting the technical standard for reliability and demonstrating a strong execution mindset. You will collaborate directly with the Head of Engineering and co-founders to architect and drive the product roadmap from an engineering standpoint.

We are looking for a leader who combines deep, hands-on technical expertise with the executive presence required to attract, mentor, develop, and retain top-tier engineering talent.

What Youll Do

Team Building & Engineering Culture

• Recruit, hire, and develop senior engineers across multiple sub-teams: cloud infrastructure, data platform, ML operations, and developer experience.
• Establish engineering standards, code review culture, on-call expectations, and a bias-toward-shipping mentality balanced with production rigor.
• Coach and grow senior/staff engineers into technical leaders; manage engineering managers as the organization scales.
  
  

• Set the 6–18 month platform roadmap in partnership with engineering teams, balancing foundational investments against product-driven urgency.
• Make high-stakes architectural decisions — build vs. buy, migration strategies, technology bets — and own the outcomes.
• Drive cross-functional alignment with product, ML/AI research, and go-to-market teams to ensure the platform evolves in lockstep with customer and product needs.
  
  

• Own production health for all platform services: incident response, postmortems, SLO tracking, and capacity planning.
• Establish and iterate on engineering practices that keep the team shipping fast without compromising reliability.
• Participate in executive-level reviews on infrastructure spend, system health, and engineering velocity.
  
  

• 12+ years of software engineering experience, with 4+ years leading platform or infrastructure teams of 8+ engineers at high-growth startups or top-tier tech companies.
• Deep, hands-on expertise in distributed systems.
• Production experience with container orchestration (Kubernetes), microservices architecture, and at least two major cloud providers (GCP, AWS, Azure).
• Strong programming ability in Go and Python; you still read code daily and can mentor engineers on systems-level design.
• Experience building quality software using AI-driven tools.
• Track record of building internal platforms from scratch that other engineering teams adopt and depend on.
• Expertise in database internals and performance tuning across SQL, NoSQL, and graph or vector data stores; working knowledge of CAP theorem trade-offs in production.
• Proven ability to hire, develop, and retain high-caliber engineers in competitive markets.
  
  

• Experience building infrastructure for AI/ML workloads: model serving, GPU scheduling, training pipelines, or inference optimization.
• Familiarity with vector databases, embedding pipelines, RAG architectures, or LLM orchestration frameworks.
• Experience operating multi-tenant SaaS platforms with strict data isolation and compliance requirements (SOC 2, GDPR, HIPAA).
• Background in real-time data streaming (Kafka, Pulsar, Flink) and event-driven architecture.
• Prior success driving large-scale cloud cost optimization initiatives (saving $1M+ annually).
  
  

• Greenfield technical challenges at the intersection of AI infrastructure and enterprise scale — you will build systems that dont exist yet.
• Direct access to founders and the CTO; your decisions shape the companys technical trajectory.
• A team of exceptional engineers from Google, Meta, Microsoft Research, and top CS programs worldwide.
• Competitive compensation, meaningful equity, and the upside of an early-stage company backed by world-class investors.