СШАPrincipal Agentic Engineer, AI Ecosystem
18 ч. назад
СШАLeadRemote
aimachine learningpython
Lead the development of AI technologies within 's ecosystem to enhance family safety and location-based services.
О компании
- ’s mission is to keep people close to the ones they love. Our category-leading mobile app, Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. serves approximately 107.7 million monthly active users (MAU), as of September 30, 2026, across more than 180 countries.
- delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basically family).
- has more than 500 (and growing!) remote-first employees. For more information, please visit .com .
- is a Remote-First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US) regardless of any specified location above.
- 's AI ecosystem is being built by three teams working from a shared 2027 vision, each owning a distinct layer:
- AI Platforms — the foundational infrastructure and company-wide AI governance: gateways and MCP connector infra, cost and spend controls, observability and safety guardrails, the agent deployment/orchestration platform, and knowledge graphs.
- AI Dev Tooling (AI DevX) — AI-powered developer tools that remove friction across the software development lifecycle: coding assistance and productivity tooling, automated and agentic testing, and the codified primitives (CLAUDE.md, evals) that make shared and monolithic repos legible to AI.
- Agentic PDLC — agents that remove humans from common, repetitive product-development work: on-call investigation, bug triage, code review, and release, consolidated under a single owner instead of being built ad hoc team-by-team.
- These teams deliberately don't own everything. A set of foundational questions — non-human identity and agent authZ, model regression eval frameworks, workflow/agent eval infrastructure, atomic agent-unit definitions, agent standards for what an agent can never do — sit in the shared space between them, ready to be addressed.
Обязанности
- We're hiring a Principal-level Agentic Engineer to hold the system view across AI Platforms, AI DevX, and Agentic PDLC — and to give the unowned middle ground between them an owner. This is not a coordination role. You'll have clear, end-to-end ownership of a defined set of cross-cutting problems, not an open-ended advisory brief. It's an architecture-and-build role for someone who can define what an "agent" is as a reusable unit at , set the standards that make agents safe and evaluable, build an ecosystem that supports our agents, and then help each team build to that architecture. In addition, this role will craft the vision for how our broad agent ecosystem will evolve into the future.
- The role operates at two altitudes, and needs to be genuinely strong at both:
- Strategic: set the technical vision for 's AI-Native developer ecosystem — the architecture that lets AI Platforms, AI DevX, and Agentic PDLC build against shared primitives instead of re-solving the same problems three times.
- Tactical: get into the core components yourself — agent execution frameworks, context and retrieval systems, eval harnesses, identity and authZ for unattended agents — and ship the parts that are too foundational to leave to any one team, or that no team currently owns.
- You'll partner closely with the AI Platforms, AI Dev Tooling, Agentic PDLC, and our Product leadership (as their technical counterpart), but you won't report through any single one of them — your mandate is the seams between all of them.
- The US-based salary range for this position is $247,000 to $363,000. We take into consideration an individual's background, job-related knowledge, skills, and experience in determining final salary. Base pay may also vary based on geographic location, with US work locations falling into one of three geographic tiers.
- Total compensation is inclusive of equity compensation in the form of Restricted Stock Units (RSUs) , as well as a comprehensive benefits package, including medical, dental, vision, financial, and other benefits.
Требования
- 12+ years of engineering experience, including deep platform or systems architecture work at consumer scale (50M+ MAU or equivalent preferred).
- Demonstrated experience architecting agentic systems in production — not just using AI coding tools, but designing the frameworks, identity models, and eval infrastructure that other agents run on.
- Direct experience with non-human identity, service-account, or agent authZ models — or a clear, well-reasoned point of view on how to build one.
- Experience designing and consuming structured interfaces for AI systems (MCP-style tool definitions, JSON Schema, OpenAPI) and building for tool-calling and contract-first agent development.
- A track record of building eval and regression frameworks for AI systems — promotion gates, scoring, and CI integration — not just running evals ad hoc.
- Strong architectural instincts across multiple services and teams, with the judgment to know which problems deserve a shared platform investment and which don't.
- Fluency in AI economics — token cost as a design constraint, progressive retrieval, and the tradeoffs between centralizing and forking model usage.
- A track record of driving technical direction across teams you don't manage — through documentation, prototypes, and demonstrated results rather than mandates.
- Excellent written communication: architecture decision records, standards, and playbooks precise enough for other engineers (and their agents) to build against directly.
Будет плюсом
- Experience building or operating an agent orchestration or deployment platform, or an MCP-style connector gateway.
- Background in ML infrastructure, model observability, or production AI systems at a company that has been through a comparable AI-native transformation.
- Experience with mobile engineering (iOS/Android) or high-throughput cloud systems, and how agent architecture needs to flex across both.
Условия
- Medical, dental, vision, life and disability insurance plans (100% paid for employees)
- Paid parental leave
- 401(k) plan with company matching program
- Mental Wellness Program & Employee Assistance Program (EAP) for mental well-being
- Generous time off: flexible PTO, companywide holidays throughout the year plus summer and winter shutdowns
- Learning & Development programs
- Equipment, tools, and reimbursement support for a productive remote environment
- Free Platinum Membership and Tile trackers
- AI Usage: We use AI to help make our hiring process efficient. That said, every hiring decision is made by real hiring teams
Другое
- We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.
- Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.
- Hold the system view across AI Platforms, AI DevX, and Agentic PDLC, so investments compose instead of collide.
- Drive build-vs-buy decisions for PDLC-critical agents, and for ecosystem-wide capabilities where an outside vendor may out-deliver an internal build.
- Build the ecosystem that supports agents as we define them today and shapes how they evolve: execution frameworks, context and retrieval systems, and telemetry that treat token spend as a first-class design constraint.
- Define what an agent is at — a reusable unit, the interface it exposes, and the standards it must meet (human-in-the-loop and blast-radius policy, eval standards, promotion gates) — in partnership with AI Platforms, who will operate the resulting infrastructure long-term.
- Design the non-human identity and agent authZ model that unblocks scheduled and unattended agents across every team.
- Stand up eval and regression infrastructure (framework, CI hooks, result storage) as a shared capability rather than three parallel bets.
- Avoid “ivory tower” syndrome by shipping production code against the highest-leverage components yourself — you're a builder first, not an advisor who hands off specs.
- Get close to live bets, such as the on-call investigation agent, to validate the architecture under real usage and economics, and prototype and de-risk the hardest pieces before asking any team to commit engineering time.
- Mentor Agentic Engineers and Staff engineers across all three teams on agent architecture, context engineering, and evaluation rigor, and help grow the senior technical bench.
- Write the architecture decision records, standards docs, and playbooks that AI Platforms, AI DevX, and Agentic PDLC can each build against independently, and represent a coherent technical point of view in build-vs-buy and roadmap discussions, even without formal authority over the teams involved.
- Our company’s mission-driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference
- Be a Good Person - We have a team of high integrity people you can trust.
- Be Direct With Respect - We communicate directly, even when it’s hard.
- Members Before Metrics - We focus on building an exceptional experience for families.
- High Intensity, High Impact - We do whatever it takes to get the job done.