Careers
By 2030, 80 million Americans will be over 65. We're building the infrastructure to keep grandma home.
Zingage builds AI agents that automate back-office operations for the largest home care companies in America: intake, scheduling, care coordination, compliance, patient engagement. All of it.
We handle half a million scheduling calls a month. Seven figures of new ARR every month. Partnerships with the largest platforms in the industry.
- Location
- New York City
- Work style
- In-Person
- Team
- ~25
Open roles
New York City · 12 openEngineering
Build the runtime beneath every agent we ship: per-decision freshness, replayable actions, HIPAA-grade governance, computer-use actuation. Four planes, each wired to a number.
New York City
The problem
Our agents act in the physical world: they fill shifts, move visits, and write to the system of record that governs care for frail patients. An agent is only as good as the runtime beneath it, and the runtime for production agents in a regulated industry does not exist yet. Building it means solving four problems your best colleagues would agree are open:
What winning means
For the world: autonomous care coordination that is auditable enough to be trusted with someone's mother. Every visit we coordinate no longer depends on stale reads, unverifiable claims, or unsafe writes.
For you: founding ownership of an entire layer: the whole runtime, all four planes, the architecture decisions, and in time the team that grows around it. The v1 of this system is already funded, owned, and in flight as our current engineering cycle; you are being hired to see what it actually is and build it into the platform every agent we ever ship runs on.
Own the first communication platform where an AI is a first-class participant: the rails, the agent-to-human handoff, and the trust surfaces.
New York City
The problem
Every communication platform ever built assumed all participants were human. Slack built work chat for people; OpenPhone built the business phone for people. We are building the first communication platform where an AI is a first-class participant, for an industry that still runs on the telephone.
That creates an interaction problem nobody has designed: the three-party primitive. A caregiver, an agent, and a scheduler share one conversation, and “who am I talking to right now” is a live product question. Threads must survive the handoff in both directions. Presence includes a machine. The agent-to-human handoff is the atomic unit of this platform, and it is where trust is negotiated in real time.
What winning means
For the world: the two million people who care for our parents get a communication system that actually respects their day: fewer interruptions, right channel, right moment, a machine teammate that knows when to stay quiet.
For you: sole ownership of the surface an entire industry touches hourly, at a company where the rails are the strategy, not a feature. And you will not be sprinting without a floor: our agent runtime provides the governance, receipts, and replay layers that make daily shipping safe, so you build fast because that foundation makes fast survivable. Together, the two seats are the halves of one thesis: context from systems, context from people.
Build the evaluation, simulation, and reliability layer for our multi-agent system. Turn every production decision into a better model.
New York City
What you'll own
- Evaluation and simulation infrastructure: CI/CD for agent behavior. Run Casey against historical scenarios, measure fill-rate outcomes, catch regressions, A/B test prompt and orchestration changes before they hit production. This is the piece that lets us ship changes to a sophisticated multi-agent system with confidence instead of vibes.
- Retrieval and grounding architecture: our agents operate over dense, agency-specific knowledge (SOPs, escalation policies, scheduling rules, compliance constraints). Design the retrieval layer that gets the right context to the right agent at the right turn, so the agent harness keeps scaling as the knowledge surface grows.
- Alignment and outcome measurement: connect every ranking decision, outreach attempt, and agent choice to downstream business outcomes (fills, retention, utilization). The event data exists across multiple systems. Nobody has unified it. You will, and everything else compounds from it.
- The agent intelligence roadmap: we have 100K+ scheduling decisions and growing with paired outcome data. You'll decide when fine-tuning, reward modeling, or new model architectures are the right next investment for the harness, and ship them.
Who you are
- An applied scientist who ships production code: your mental model of system behavior is probabilistic, but your output is working systems.
- Fluent in the full stack of interventions (prompting, retrieval, evals, fine-tuning, RL) and have the judgment to know which to reach for.
- Someone whose first instinct when something breaks is to design an experiment, not just read a stack trace.
- Comfortable with the reactive trap dying. You stop treating symptoms and start building the systems that prevent whole classes of problem.
Build the data platform underneath Casey: outcome instrumentation, real-time event backbone, canonical EMR models. Path to Head of Data Platform.
New York City
What you'll own
- The outcome data layer, the instrumentation connecting every agent decision to customer-level business metrics: client retention, caregiver satisfaction, authorization utilization, hours erosion. The foundation for everything our AI/ML work depends on, every ROI claim we make to customers, and every experiment we run.
- The real-time event backbone: visit status changes, clock-ins, call-outs, ranking decisions flowing as events any system can consume in real-time. This is what makes the EMR polling and rate-limiting problems structurally go away instead of being band-aided.
- The integration platform: canonical data models across WellSky, HHAeXchange, AlayaCare, and Axxess so that adding EMR #5 is configuration, not 30+ bespoke commits. Also the foundation for RCM: you need unified authorization and billing models before you can build agents that optimize revenue.
- Analytics and experimentation tooling: warehouse architecture that makes it trivially easy for any engineer to answer "did this change improve customer outcomes?" without writing a custom query every time.
Who you are
- Humble about and genuinely excited by the unglamorous work: data pipelines, ETL, cleaning up messy EMR data, building the joins nobody has written. You see the invisible infrastructure the way a great plumber sees plumbing.
- Opinionated about data modeling as a craft. FHIR standards, canonical visit/authorization/billing models: "here's how these entities should relate, and here's why this model compounds downstream."
- AI-native and technologically curious. A critical field only exists as free text in an EMR web portal? You think: could we use an LLM to parse it into structured data with validation? No API? You think about browser agents. You spot opportunities to apply new capabilities to data infrastructure problems.
12-week internship. AI, data platform, or product track. You're treated as a real engineer from day one.
Remote (US)
What we look for
- Obsession. Have you built something because you couldn't stop thinking about it? Side projects with real users. Open-source contributions where you went deeper than the issue asked. Evidence of staying up until 3 AM because the problem was interesting, not because someone assigned it.
- Technical fundamentals. Strong CS fundamentals. Comfortable in TypeScript. You use Claude Code as a force multiplier, not a crutch: you catch when the AI gives bad output and fix it.
- Learning velocity. When you encounter something you don't know, how fast do you figure it out? The take-home tests this directly: you're dropped into a real EMR integration or a real AI scheduling dataset and need to make sense of it.
- Communication. The Loom walkthrough in the take-home tests whether you can explain your thinking clearly. An engineer who can build but can't communicate what they built and why is only half useful.
What you'll do
You'll work with a mentor to scope a project in week 1, then own it end-to-end. You're a real engineer on the team: standups, production ships, code review, real deliverables. The track emerges based on your strengths and where the team needs help most.
Deployment & Ops
Build repeatable deployments, dependable support, and lasting customer relationships. A hands-on leadership role with a path to Chief Customer Officer.
New York City
What you will own
- Personally run deployments, learn where customers and the team get stuck, and turn those lessons into playbooks that others can run.
- Make every account's stage, owner, next step, and blocker visible. Define what a successful launch means and verify it with the customer.
- Lead the team: allocate work, coach people, plan coverage, and make staffing decisions grounded in workload and customer needs.
- Build a quarterly improvement roadmap. Choose which customer segment or operating constraint to solve first, what to defer, and what support you need from Product and Engineering.
What you bring
- You have personally built or substantially improved a repeatable onboarding, deployment, or service operation. You can show what changed in time to value, effort, quality, or retention—and explain your own contribution.
- You have managed people and capacity while maintaining delivery. You can make a staffing plan, develop teammates, and make clear tradeoffs when demand exceeds resources.
- You can connect frontline problems to a sequenced roadmap, including the work you chose not to do.
- You still enjoy hands-on customer and operational work. You are comfortable starting with a small team and incomplete infrastructure.
Take a portfolio of home care agencies from signed to running: kickoff, configuration, testing, go-live, ramp. Make the next launch faster than the last.
New York City
What you'll own
- Signed to live to running, on time. Run the kickoff. Coordinate configuration. Run the channel and escalation tests. Train managers and frontline staff. Hold the date.
- The weekly rhythm across your portfolio. You know where every account stands before it tells you, and the quiet ones don't stall.
- Adoption past go-live. You watch for drift and step in before a small problem becomes churn.
- First-line triage. You resolve what you can and route what you can't, so engineering sees patterns instead of noise.
What we're looking for
- Deployment execution. You've run onboardings end to end. You held a go-live date, trained a frontline team, and drove an account through adoption. The workflow stuck because you ran the change, not because you handed off a deck.
- Portfolio management. You've carried many customer motions at once and you set the priority. You don't wait for the escalation.
- Customer presence. In one week you run a review with an agency owner, train a scheduler, and handle an escalation. The customer never feels like they are managing you.
- Pattern recognition. You notice when the same friction appears across accounts. You ask why. You feed it back in a way Product can act on.
Go-to-market
Own the revenue number and build the machine behind it: SDR and AE hiring and ramp, quota and comp design, pipeline rigor, and the next stage of growth.
New York City
What you'll own
- The number, and the funnel math that gets us to it.
- Hiring, ramp, and coaching for the SDR and AE bench. You coach daily, not quarterly.
- Quota design, comp plans, territory and account strategy.
- Pipeline rigor: stage definitions, forecast accuracy, and an honest view of what is real.
What we're looking for
- Builder-manager: you have built a high-velocity SMB sales motion, not just managed one. You hired and ramped reps, owned a team number, and can prove per-rep production rose while you ran it.
- Founding AE or first sales hire at a startup that scaled: you built the early playbook and have managed, or are clearly ready to.
- Numerate. You reason in funnel math, not headcount spreadsheets.
- You still like selling. If your last few years were spent managing through dashboards, this is the wrong seat.
Full-cycle closing with home care agency owners at SMB velocity. SDR-fed pipeline plus your own. Founding seat on the sales org.
New York City
What you'll own
- A monthly new-business quota that we share on the first call.
- Discovery that gets the messy truth out of an owner: what breaks on a Friday night, what it costs them, and who else has to agree.
- The demo. You run our product against the agency's actual problem instead of a feature tour.
- Self-sourced pipeline alongside SDR-fed meetings.
What we're looking for
- Proven closer: experience closing SMB or mid-market new business in a high-velocity motion, with attainment, rank, and receipts.
- Top SDR stepping up: proven outbound production plus real closing exposure. The live demo session decides.
- The shape either way: a discovery-led closer who owns a number, runs tight meetings, and builds some of their own pipeline.
- You want SMB velocity. If you need long sales cycles and a sales engineer in every call, this is the wrong seat.
Phone-first outbound to agency owners who answer their own phones. Cold calls, conferences, field visits. The last person in this seat is now an AE.
New York City
What you'll own
- 8-10 qualified meetings held per week, quality-weighted: an AE has to accept the meeting and the pain has to be real and recorded.
- Your own target list. You research the agency before you dial and you know why you are calling this owner today.
- Cold calling as the primary channel, with email, LinkedIn, and creative plays supporting it.
- The field motion: conferences in spring and fall, plus regular agency visits.
What we're looking for
- Proven producer: outbound SDR or BDR work with production you can prove through quota definition, attainment, rank, and sourced pipeline. SMB owner-operator motions are the best preparation for this buyer.
- Exceptional builder: you have measurable production you generated yourself somewhere else. Wealth management, insurance, recruiting, fundraising, hospitality, founding a company, building your own training book, competitive sport. Bring the numbers.
- The shape either way: warm, plain-spoken, high-activity, coachable. Someone an agency owner enjoys buying from, not a polished enterprise rep.
- You want a phone-first, rejection-heavy job. This is the whole job, not a short stage you pass through.
First marketer. Field, lifecycle, content, and paid experiments that multiply a sales motion which already works.
New York City
What you'll own
- Pipeline contribution: meetings held and opportunities created, with denominators you can defend.
- Field and events across the spring and fall home care conference circuit.
- Lifecycle and email: onboarding, nurture, reactivation of dormant pipeline.
- Content that arms sellers: what an AE sends after a demo, and what an owner forwards to their partner.
What we're looking for
- Early-stage growth builder: experience running demand generation or growth at a startup, with campaigns tied to pipeline numbers. First or early marketing hire is a plus.
- Sharp specialist stepping up: deep strength in lifecycle, field, or content, plus evidence you can own the whole board.
- The shape either way: a full-stack builder with revenue receipts who writes well, measures honestly, and ships without being asked.
- You talk in meetings held, not MQLs.
Talent
Build the recruiting engine that doubles our team in 90 days. You are the function.
New York City
You own
- The entire recruiting function: sourcing, screening, closing. You are the function until you build the team
- Proactive pipeline for ~10 open roles across engineering, AI/ML, product design, enterprise sales, and GTM
- Workforce planning with functional leaders: you sit with eng, sales, and ops to anticipate what they need next quarter, not just what they need today
- The outbound engine that replaces our dependency on contingent recruiters
You are
- Someone who has sourced and closed at a company that was growing fast enough to break things: Ramp-speed, Uber-speed, not steady-state hiring
- A builder. You've done the grind: high-volume sourcing, cold outreach that converts, agency-level hustle. But you've also seen how an in-house function scales
- Opinionated about quality. When a hiring manager says "I need a senior engineer from Google," you say "let me show you why this person from a 10-person startup is better," and you're right
- Obsessive about pipeline. You don't wait for a req to open before you start building relationships with people you want
“We left jobs people don't leave to build infrastructure for the people nobody builds for. If that trade makes sense to you, we should talk.”
— Daniel Tian & Victor Hunt, founders of Zingage
The team
Currently shippingWe handle half a million scheduling calls a month.
Ex-Uber, ex-Ramp, ex-Citadel. People who could be at any company in tech, and chose the hardest problem nobody else wants to touch. Not because they ended up in healthcare by default. Because they looked at 80 million aging Americans and decided someone has to build the infrastructure. Might as well be them.
Team from
Backed by
~25 people. Everyone either builds or sells, usually both. The GTM person writes SDR agents. The engineer presents to the customer's board. Nobody watches from the sidelines.
Our values
Customers first
“Every line of code now has a patient on the other end. A race condition here means a missed visit.”
We deploy to customer sites. We shadow schedulers. We watch the system run. Then we ship improvements from what we observe.
Velocity
“7 product improvements in 6 days. Every one from sitting in a branch office watching the system run.”
New enterprise customers every month. Partnerships launching with the two largest platforms in home care. The pace is the product.
In-person, in the arena
“You can't build for the real world from a laptop in your apartment.”
We work together in New York City. We fly to customer sites. The best ideas come from being in the same room, and from being in the field.
Extreme ownership
“We don't make excuses. We don't blame anyone or anything.”
You'll own entire deployments end-to-end. Fly to the customer, build the integration, present to their board, ship product from the field.
Life here
Soho, New York- Real equity
- Competitive base and meaningful ownership. If this works, it should work for you.
- Equipment stipend
- Whatever setup makes you fast.
- Luxury gym membership
- We work in health care. Yours counts too.
- Lunch daily, dinner late
- Lunch every day. Dinner when work runs past dark. Big fan of late-night jams!
- Time off as needed
- Take what you need. We measure output, not hours at a desk.
- Soho office rituals
- Happy hours, poker nights, and builder events.
You can tell a lot about a company from its snack shelf. Ours: Gruns gummies, sardines, protein bars, midday froyo runs.
Read more
Anthropic, ElevenLabs, and the sharpest analyst in healthcare AI have all written about the work. Read theirs before ours.
How Zingage automates care coordination for 400+ agencies
How Claude powers the reasoning layer behind staffing, care coordination, and compliance, and cut after-hours labor 82%.
82% after-hours labor reductionReadWhy home care needs an AI operator, not another workflow tool
An independent deep dive on why home care's operating layer is broken, and why fixing it takes an operator rather than another workflow tool.
7 minute readReadZingage supports 3X more home care calls with ElevenAgents
How Zingage runs 24/7 phone coverage that knows when to handle a call autonomously and when a human needs to hear it.
3X call volumeRead