About Neo
AI is the most significant shift in how work gets done since the advent of the Internet — yet most organizations fail to capture its value. Neo is changing that.
Founded by Bhavin Turakhia — Co-Founder of Zeta, Radix, and Titan — Neo is building an integrated, AI-first suite of products that capture work, centralize context, and make AI a first-class participant in every workflow:
Tasket — A radically reimagined, AI-native work management platform that centralizes context and makes AI delegation seamless for all work.
Friday — AI Assistant, co-worker and agent platform, pre-integrated into Tasket, Studio, Drive and 1000+ SaaS platforms.
Studio — AI-native suite for co-creating docs, spreadsheets and diagrams collaboratively with humans and agents.
Scribe — AI assistant for meetings that goes beyond note-taking and actually does your work while on the call.
About the role
As Technical Architect you will own the architecture of the Neo suite end to end — backend and frontend — and set the technical direction other teams build against.
We are proponents of leveraging best-in-breed AI tools at every step of the engineering lifecycle — design, development, review, and testing. This requires a different engineering mindset: a lean team of senior, hands-on, AI-adept engineers, resulting in ultra-rapid iteration cycles and fast output. You will own, oversee, and set the bar for this approach across the systems you architect, from design through to production.
This is a role for a proactive, independent decision-maker who reasons from system internals up to company-wide architecture, and who is the final word on the hardest trade-offs the platform makes.
Responsibilities
Architecture & technical direction
Own the architecture of the Neo suite — service boundaries, data models, and the frontend/backend contracts that hold it together as it scales.
Decide the cross-cutting reliability, performance, and security trade-offs that no single team owns, and set the direction other teams build against.
Define the platforms, reusable libraries, and standards that keep the codebase consistent across teams.
Execution & delivery
Drive delivery end to end on the hardest problems: turn a spec into shipped software by breaking it down, running agents in parallel to implement, and steering them to a working result.
Own verification — the real bottleneck in an agentic workflow. Decide what "correct" means at the system level and hold every team to it before anything reaches production.
AI-first SDLC harness
Build and evolve the harness the whole engineering org builds with — specs, reusable skills, subagents, evals, and guardrails that let many agents run in parallel and produce consistent results regardless of the underlying tool.
Set the quality gates that agent-authored change must pass before a human reviews it, and tighten them as new failure modes surface.
Mentoring & raising the bar
Mentor senior and staff engineers, run design reviews, and turn what works into standards, templates, and paved roads adopted org-wide.
Spread good agent practice across teams so the whole org's leverage compounds, not just your own.
Product thinking
Work with product and engineering leadership to pin down the right problems before committing engineering effort — scope feasibility, surface trade-offs, and push back when the cost isn't worth the outcome.
Own outcomes at the platform level, not tickets or a single team's roadmap.
Skills
AI-native engineering practice — Fluent in an agentic workflow: spec-driven delivery, steering coding agents, and building the harness (specs, skills, evals, guardrails) that makes agent output reliable across the whole engineering org.
Strong language & runtime fundamentals — Deep proficiency in one or more of the languages Neo works in — Java, Python, TypeScript/JavaScript, Go — including OOP and design, concurrency, memory management, and how the runtime behaves under load.
System internals — Working mastery of processor, memory, network, and storage internals, and how to write code that uses hardware well and avoids bottlenecks.
Distributed systems — Fault modelling, concurrency, isolation, consensus, time/clocks and ordering of events, rate control, and load distribution — the judgment to architect for scalability, reliability, and security at company scale.
Internals of core infrastructure — Hands-on with the internals of systems like Kafka, Cassandra/Scylla, and Redis — enough to troubleshoot, tune, and make the build/use calls other teams follow.
Scale & multi-homing — Experience designing for multi-region, multi-cloud, or high-volume data processing and storage, with an eye on cost per GB and tight p99 latency.
Frontend & full-stack judgment — Comfortable making architectural calls on both sides of the stack — state management, real-time collaboration, and the contracts between service and UI.
Orchestration & protocols — Kubernetes and containerised deployment; low-level network protocols (gRPC, HTTP/2, QUIC).
Troubleshooting & performance — Diagnosing memory issues, GC tuning, and resource leaks; keeping systems stable and efficient under load.
Delivery engineering — Branching strategy, build, deployment, and CI/CD practices that keep an entire org's delivery fast and high-quality.
Cloud — AWS / Google Cloud / Azure (OpenStack where relevant).
Experience & Qualifications
15+ years in software development and delivery, with a track record of architecting systems at scale across multiple teams or products.
Production experience across a modern, polyglot stack (e.g. Java, Python, or Node/TypeScript) with REST, SQL (PostgreSQL/MySQL), messaging systems, and microservices.
Engineering degree in computer science or equivalent.
Equal Opportunity
Neo is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We encourage applicants from all backgrounds, cultures, and communities to apply and believe that a diverse workforce is key to our success.