Principal Engineer

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.

Drive — AI-native repository, where humans and agents can co-work on files.

Scribe — AI assistant for meetings that goes beyond note-taking and actually does your work while on the call.

About the role

As a Principal Engineer you will own the design and architecture of the suite and mentor engineers across teams.

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 and oversee this approach for the systems you lead, from design through to production.

This is a role for a proactive, independent decision-maker who is at home reasoning from system internals up to cross-team architecture, and who raises the bar for what both people and agents ship.

Responsibilities

Architecture & technical direction

• Own the architecture of Neo's backend services and frontend components — service boundaries, data models
• Resolve cross-cutting reliability, performance, and security concerns
• Build platforms, reusable libraries, and utilities that make the team faster and the codebase consistent.

Execution & delivery

• Drive delivery end to end: 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 for a system and make sure what ships actually meets it, before it reaches users.

AI-first SDLC harness

• Build and improve the harness the team builds with — specs, reusable skills, subagents, evals, and guardrails that let many agents work in parallel and give consistent results regardless of the underlying tool.
• Set the quality gates that agent-authored changes pass before a human reviews them, and improve them as failure modes show up.

Mentoring & raising the bar

• Mentor engineers and run design reviews; turn what works into standards, templates, and paved roads the whole team uses.
• Spread good agent practice across the team so its leverage compounds, not just your own.

Product thinking

• Work with product to pin down the right problem before building — scope feasibility, surface trade-offs, and push back when the cost isn't worth the outcome.
• Own outcomes, not tickets.

Skills

• AI-native engineering practice — Fluent in an agentic development workflow: spec-driven delivery, running and steering coding agents, and building the harness (specs, skills, evals, guardrails) that makes agent output reliable at the team level
• Strong language & runtime fundamentals — Deep proficiency in one or more of the languages we work in — Java, Python, TypeScript/JavaScript, Go — including OOP and design, concurrency, memory management, and how your runtime behaves under load. Comfortable picking the right language for the job rather than defaulting to one.
• System internals — Working knowledge of processor, memory, network, and storage internals, and how to write code that exploits hardware well and avoids bottlenecks.
• Distributed systems — Fault modelling, concurrency, isolation, and consensus; time, clocks, and ordering of events; rate control and load distribution. Strong design and problem-solving instincts for performance, scalability, security, and reliability.
• Internals of core infrastructure — Hands-on with the internals of Kafka, Cassandra/Scylla, and Redis — enough to troubleshoot, tune, and make sound usage decisions.
• I/O-optimised algorithms — Asynchronous and non-blocking I/O and DMA, for high throughput in performance-critical paths.
• Hosting & orchestration — Kubernetes and containerised deployment of cloud-native applications.
• Low-level network protocols — Familiarity with gRPC, HTTP/2, and QUIC.
• Troubleshooting & performance — Diagnosing memory issues, GC tuning, and resource leaks to keep systems stable and efficient under load.
• Delivery engineering — Branching, build, deployment, and CI/CD practices that keep delivery fast and high-quality.
• OOAD & algorithms — Object-oriented analysis and design and efficient data structures for well-structured, maintainable, performant systems.
• Cloud — AWS / Google Cloud / Azure (OpenStack where relevant).

Experience & Qualifications

• 8+ years in software development and delivery, with a track record of architecting systems at scale.
• Production experience across a modern stack — e.g. Java, Python, or Node/TypeScript — with REST, SQL (PostgreSQL or 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.