Who gets hired and onto which teams
Ellipsis Health is an AI healthcare company, but the people doing the hiring are not looking for AI generalists. They want builders, sellers, and clinicians who can land Sage (the company's emotionally intelligent voice agent for care management) inside health plans, health systems, specialty-care providers, and pharma. Roughly 100 employees support that mission from San Francisco, and the open-roles list tells you, function by function, who the company needs next: senior engineers who can ship into regulated healthcare workflows, two VP-level sales leaders to crack payer and provider markets, and a small data team to keep the clinical science honest. That mix (engineering, enterprise sales, data/ML, customer success) is the only door open right now.
Engineering dominates the hiring slate. Of the 16 live direct-apply postings tracked in early September 2026, 11 sit in engineering: Senior Backend Engineer, Forward Deployed; Senior Backend Engineer, AI Evaluations; Senior Backend Engineer, Infrastructure; Senior ML Engineer, Agentic AI; Senior DevSecOps Engineer; Senior QA Engineer, Forward Deployed; Senior Full Stack Engineer, Core Services; Senior Software Development Engineer in Test (SDET), Salesforce. Sage is an agentic AI product running inside regulated healthcare workflows, so Ellipsis Health needs backend engineers who can ship forward-deployed integrations into customer environments, ML engineers who can harden an LLM-driven voice system, and DevSecOps and QA people who can keep the whole thing HIPAA-compliant. Recent postings on Zero G Talent's job board list 15 salaried roles with a band running from $128,000 to $250,000 and a median around $210,000. The public slate confirms a senior-skewed engineering org, where 11 of 16 openings carry a "Senior" prefix.
Sales and customer-facing roles come next, and the two most senior searches on the board say a lot about stage. Ellipsis Health is recruiting a VP Provider Sales ($160,000–$210,000) and a VP Payer Sales ($180,000–$220,000) simultaneously, alongside a Director of Customer Success. Two VPs plus a director is the footprint of a company moving from pilot deployments to multi-segment enterprise contracts. The "payer" and "provider" split maps directly to the customer base Sage already serves: CVS Health, Optum, Duke Health, Nemours Children's Health, Strive Health, Equality Health, Virta Health, Guardant Health, Agilon Health, CVS Caremark, and Genworth all appear on the company's site. Payer sales hires chase health plans; provider sales hires chase health systems and specialty-care groups. Candidates for either seat are expected to have already sold into those buyers.
Data and analytics round out the mix, and this is where the company is growing fastest. The most recent 28 days added two new data-analytics roles and one engineering role; a Senior Data Scientist (San Francisco) and Senior Data Platform Engineer ($150,000–$170,000) are both live. For a company whose founding science is speech-based clinical assessment of depression, anxiety, and stress, data scientists are not back-office. They keep Sage's sensitivity and specificity in the 80s and push the model toward the next vital sign. A Forward Deployed Product Manager, AI Assistant ($100,000–$165,000) is the connective tissue between that data work and the customer, sitting between ML, backend, and a health plan's clinical operations team and translating between them.
Two practical details shape who actually clears the resume screen. The board data and public postings both put nearly every opening in San Francisco with a hybrid expectation, even though Engradar's tracker estimates roughly all roles are remote-eligible. Candidates should expect to be on-site in the Bay Area at least part of the week. And because scammers have impersonated Ellipsis Health in fake job posts (a warning the company posts on its own careers page) every applicant should verify the posting lives on ellipsishealth.com before sharing personal information.
What it pays
Compensation mirrors the hiring mix. Engineering fills nearly 70% of the 16 open roles, with product and sales picking up the rest, and the money follows that weighting. Across recent postings on Zero G Talent's job board, the 15 salaried roles carry a band of $128,000 to $250,000, with a median around $210,000 — a figure that signals the company pays at senior-IC rates rather than across-the-board tech-industry norms.
Senior engineering bands cluster at the top of that range. Five openings — DevSecOps, ML Engineer for Agentic AI, Backend for AI Evaluations, Backend for Infrastructure, and Backend Forward Deployed — each list $175,000 to $250,000. The Senior DevSecOps Engineer posting sits at $160,000 to $250,000, the widest spread on the board and a sign that security specialists with platform-level experience can push toward the ceiling. The Senior Data Scientist role carries the most compressed band at $180,000 to $230,000, which tracks with how narrow data-science leveling tends to be once you filter for senior candidates. A separate Ashby posting for a Senior SDET on Applications (Ellipsis Health's quality engineering track) lists $140,000 to $160,000, the only public engineering number that lands well below the rest and likely reflects a different leveling rubric.
| Role | Band (USD/yr) | Location |
|---|---|---|
| Senior DevSecOps Engineer | $160,000–$250,000 | San Francisco – Hybrid |
| Senior ML Engineer, Agentic AI | $175,000–$250,000 | San Francisco – Hybrid |
| Senior Backend Engineer, AI Evaluations | $175,000–$250,000 | San Francisco – Hybrid |
| Senior Backend Engineer, Infrastructure | $175,000–$250,000 | San Francisco – Hybrid |
| Senior Backend Engineer, Forward Deployed | $175,000–$250,000 | San Francisco – Hybrid |
| Senior Data Scientist | $180,000–$230,000 | San Francisco – Hybrid |
| Senior SDET, Applications | $140,000–$160,000 | San Francisco – Hybrid |
The pattern across the bands is consistent: senior engineers and data scientists earn in the high six figures, with the ceiling reserved for staff-level scope around AI evaluation, agentic systems, and infrastructure. Forward-deployed titles (Backend and QA variants) pay the same as their platform counterparts, a useful signal for candidates weighing whether to take a customer-facing rotation. Ellipsis Health does not publish equity grants, bonus targets, or benefits detail on its Ashby postings or careers page, so any offer-level specifics on those points come from recruiter conversations rather than public listings. Hitting the midpoint of a $175,000–$250,000 band puts base comp around $212,500, comfortably above that $210,000 figure and inside what a senior engineer with five-plus years should expect from a healthcare-AI company at this stage. Negotiating room concentrates at the top of each band and tends to favor candidates who can point to prior work on production LLM systems, voice agents, or clinical-grade data pipelines — the technical surface area Sage depends on.
What the hiring process actually looks like
The pipeline for technical roles is short by design. Glassdoor interview reviews describe candidates moving through four rounds (HR, two coding sessions, and a final with an engineering lead) over a roughly two-week timeline, starting from an online application. The compressed cadence signals that the company isn't running candidates through a battery of behavioral interviews; it compresses the evaluation into a handful of decisions that mostly land on the technical axis. Preparation time should concentrate on coding fluency and architectural judgment rather than rehearsing a dozen career narratives.
The first conversation is with HR and functions as a screen for fit, logistics, and baseline competency. After that, two coding sessions dominate the schedule. One Glassdoor review describes one of those rounds as a take-home-style challenge assigned within a day: candidates receive the problem, complete it, and return it for evaluation. The pairing of a written challenge with live coding conversations is consistent with how small, applied-AI teams evaluate senior engineers: the take-home surfaces sustained problem-solving and code quality in a realistic artifact, while the live sessions pressure-test how candidates reason through unfamiliar problems in conversation. The final round, run by the engineering lead, is where the accumulated signal gets read together. The team's senior technical decision-maker is the last voice in the room, not the first.
Screening criteria aren't documented publicly beyond these reviewer accounts, but the role mix on offer tells you what the bar is calibrated for. The current board listings cluster around two skills: production-grade software engineering and applied machine learning on real clinical data. Candidates who can demonstrate both, even in small projects, will read as a closer match on paper than a pure researcher or a pure web engineer would.
Behavioral criteria that get candidates through are inferred from the company's stated positioning. Ellipsis Health's published work emphasizes a clinical-aid framing: CEO Mainul Mondal has described the product as "a buddy for health teams" and "an adviser for behavioral health," with clinicians retaining all care decisions. Candidates who can articulate that division of labor — building AI that flags risk while leaving diagnosis and treatment to licensed clinicians — are likely to land more cleanly than candidates who position the technology as autonomous. A candidate who claims their model can replace a psychiatrist will read as a poor fit regardless of how well they code.
One practical hazard deserves its own warning. Ellipsis Health's careers page flags that fraudulent job postings have appeared under its name and instructs applicants to confirm any outreach by emailing [email protected] directly. Anyone moving deep into the funnel should treat unsolicited LinkedIn messages or third-party job-board solicitations claiming to be from Ellipsis as suspect until verified — the legitimate four-round process is initiated by the candidate's application and never involves payment, identity documents, or off-platform chats. The fastest way to confirm a real process is to cross-reference any recruiter email against that address and the open roles listed there.
The whole sequence (apply, HR screen, two coding rounds, engineering-lead close) runs fast enough that a candidate can expect a definitive answer inside two weeks if they're being moved forward, or silence in roughly the same window if they aren't.
Where the work happens
Ellipsis Health runs its operations out of San Francisco. The company was founded there in 2017 and remains headquartered there, building machine-learning systems that detect and measure symptoms of anxiety and depression through the way people speak. The 2025 launch of Sage, its emotionally intelligent AI Care Manager, was announced from San Francisco and references the team's local clinical and engineering roots.
Every active posting on the company's hiring board lists San Francisco as the worksite — "San Francisco – Hybrid," applied uniformly across roles that include Senior DevSecOps Engineer, Senior ML Engineer (Agentic AI), Senior Backend Engineer (AI Evaluations, Infrastructure, and Forward Deployed), and Senior Data Scientist. No posting lists a remote-only option, and none cites a location outside San Francisco. For candidates outside the Bay Area, the practical question is relocation: the company does not advertise remote-first flexibility for any of its open engineering roles. That posture aligns with a clinical-AI product that depends on tight iteration with healthcare partners and on in-house expertise to train and validate vocal biomarkers, but it narrows the funnel geographically. Anyone considering an application should plan for a San Francisco commute, a relocation conversation, or a pass.
What "hybrid" looks like in practice
The board describes each role as hybrid without specifying which days employees are expected on-site. That ambiguity is common in early-stage health-AI companies, where the answer usually depends on the team's cadence — sprint kickoffs, customer pilots with health systems, and clinical-advisory meetings pulling engineers in, while quiet weeks of model training pull them out. For a company whose Empathy Engine trains on millions of live clinical patient calls, some in-person collaboration with clinical staff and partners is structurally hard to replace. The $45 million Series A the company closed in June 2025 — PR Newswire reported that round, led by Salesforce, Khosla Ventures, and CVS Health Ventures — was earmarked partly for "enhancing clinical integrations," which suggests more, not fewer, joint working sessions with health-system partners in the months ahead.
Salesforce, the lead investor in that round, also underpins Sage: the product is built on Salesforce's Health Cloud, meaning a meaningful slice of engineering work happens alongside Salesforce-adjacent technical staff rather than purely inside Ellipsis's four walls. CVS Health Ventures' involvement puts the company within talking distance of one of the largest US payers — useful for a product positioned to help clinicians manage high-risk, high-cost members. A 2022 partnership with Tiatros integrated Ellipsis's vocal biomarker technology into Tiatros' behavioral health platform, extending the company's reach into employer, payer, and government channels alongside the direct health-system and pharma contracts.
Who thrives here
Ellipsis Health's employee reviews are short, repetitive, and unusually warm — the kind of feedback loop that says less about polish than about a small team that hasn't yet developed the friction of a larger org. Three patterns surface across the Glassdoor footprint.
The first is self-direction paired with flexibility. Glassdoor reviewers note that Ellipsis Health offers flexible work schedules that give employees independence and enable working during their peak performance hours. That framing matters — it's not a perk headline, it's a job description. Candidates who treat flexibility as a synonym for "I'll log in whenever" tend to wash out in environments like this; the people who thrive use the latitude to ship during their sharpest windows and still hit the team's shared milestones. With 15 salaried roles on the Ellipsis Health board right now, most of them hybrid in San Francisco, the company doesn't have the headcount redundancy to absorb someone who disappears for a week and surfaces with a half-finished PR.
The second is comfort with role blur. Glassdoor's own summary notes that employees at Ellipsis Health learn a range of skills by wearing a lot of different hats. For a Senior ML Engineer working on agentic AI or a Senior Backend Engineer sitting across that same mix, that ambiguity is the job, not a side effect of it. The roles on the board don't sit in neat lanes. A single posting can pull in DevSecOps instincts, data-science rigor, and customer-facing deployment in the same week. Engineers who want a fixed scope and a tidy backlog find that frustrating; engineers who can switch contexts without losing rigor find it energizing.
The third is ownership that shows up in the product. The Glassdoor overview captures it in one line: "Opportunity for ample growth and your impact is visible." In a small company shipping into healthcare — a regulated, slow-moving space where a behavioral-health AI has to clear clinical and privacy bars — the distance between an engineer's pull request and a patient's experience is shorter than at almost any larger competitor. People who need that line of sight, and who can carry the weight of it without freezing, do well. People who need three layers of management to tell them their work mattered do not.
The social texture matters too. Reviews describe "nice people you'd like to work with - chill and relaxed, accommodates people of all backgrounds and timezone," a "solid data science team," and "everyone is helpful." Another put it more directly: "Work/life balance is great. Everyone is helpful." That's a culture signal worth taking seriously — collaborative without being performative. Candidates who interview by hogging the whiteboard, or who need to be the loudest voice in every standup, will read that room wrong on the way in.
There is one honest counterweight. The same reviewer who praised the flexibility also flagged the catch: maintaining a healthy work-life balance is a challenge. When your peak performance hours are yours to choose, the off-hours are yours to defend too. The people who thrive at Ellipsis Health treat that boundary as part of the job — not a reward they cash in after burning out.
If you're the kind of engineer who wants a narrow title, a fixed stack, and a manager who pings you at 9:01 a.m., this isn't your shop. If you'd rather own a slice of a behavioral-health AI end-to-end, set your own hours, and see your code land in front of clinicians within the same quarter — start with the Senior Backend Engineer, AI Evaluations or Senior ML Engineer, Agentic AI postings, read the Glassdoor reviews yourself, and bring evidence of cross-scope ownership to the loop.
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