Who Gets Hired, and Where They Land
AKASA's $120 million Series C in June 2024, LeadIQ's figures put the Series C at $120 million, didn't just fund product launches — it rewrote the hiring map. The company now employs roughly 240 people across five continents, LeadIQ's data shows, on $205 million total capital, LeadIQ reported, and the capital allocation shows in the requisition mix: engineering, product, program management, sales, and customer delivery are absorbing headcount while finance, legal, and G&A hold steady. The interview loop screens for demonstrated technical depth and mission-aligned traits. Candidates who understand the hiring mix, the compensation band, and the screening bar can prepare accordingly and position themselves strongly.
Zero G Talent's board shows ten salaried roles posted recently across six functions, a spread that maps cleanly to the product suite's expansion from prior authorization into coding, CDI, and denial management. Engineering carries the largest share: a Backend engineer and a DevOps engineer in South San Francisco, plus a Machine Learning Engineer designated remote across the United States. The LeadIQ directory confirms the depth — a Head of Cloud Infrastructure, a Senior Software Engineer, and a co-founder labeled "R&D" all sit on the technical side.
This isn't a team maintaining a legacy stack; they're training health-system-specific LLMs on clinical and financial data, deploying custom models the company says outperform GPT-4 by 38 percent, PRNewswire found, on prior authorization document selection.
Product and program management sit beside engineering. A Senior Product Manager role in South San Francisco appears alongside a Senior Technical Program Manager in the same location, while a Head of Product Marketing rounds out product-facing leadership. The pairing makes sense: each health system gets a customized model, so product managers aren't just shipping features — they're scoping data pipelines, integration points, and clinical validation workflows that differ customer to customer.
Sales shows up as a single Director role, remote across the United States, but the function's footprint is larger than one headcount suggests. The LeadIQ roster includes an Associate Director and a Director of Customer Engagements, titles that straddle post-sale expansion and pre-sale technical validation.
In enterprise RCM, the line between "sales engineer" and "customer success" blurs; AKASA's deployment model, which trains models on each client's own data, demands technical fluency throughout the commercial motion.
Customer-facing delivery gets explicit representation. Those two Customer Engagement leads sit alongside HR and recruiting operations specialists (two Senior HR Managers and a Senior Recruiting Operations Specialist), a ratio signaling the company is investing in onboarding capacity, not just headcount volume.
For a platform that embeds into Epic and Cerner workflows and navigates payer portal fragility, implementation talent is a product constraint, not a support function.
The remaining functions appear in the directory but not the recent postings: finance, legal, and executive leadership (two co-founders, a CEO, a CTO named in press materials). That absence is informative: AKASA isn't building out G&A at the same clip as product and engineering.
A $100–250 million revenue estimate, according to LeadIQ, and the Cleveland Clinic systemwide expansion suggest the commercial engine is running; the hiring energy points at the technical and delivery capacity needed to fulfill contracts already signed.
For a candidate, the read is straightforward. If you write production-grade backend systems, operate Kubernetes at scale, or train LLMs on messy, private healthcare data — there are open doors.
If you translate clinical workflows into product requirements, manage cross-functional delivery against payer integration timelines, or run technical sales cycles with health system CFOs and CIOs, there are open doors.
If your background sits in pure research, generalist marketing, or early-stage startup operations without healthcare domain depth — the current mix suggests a tighter filter.
What the Roles Pay
AKASA's compensation sits in the upper tier for early-stage AI healthcare companies, but the numbers depend heavily on which dataset you trust. The company's own job postings show a tight band: $139,000–$231,000 median total cash, median $203,000, across ten salaried roles posted recently.
Hireoven's scrape of 13 live U.S. listings aligns closely: median $187,500, 25th percentile $160,000, 75th percentile $202,500, full posted range $60,000–$240,000. Levels.fyi, which leans on user-submitted offers from candidates further along in the process, reports a higher median of $177,000 and a top end of $288,550 for a Product Manager at the "Common Range Average" level. Glassdoor and Salary.com tell a different story, with averages around $66,000–$68,000, but those figures appear to blend in non-technical or older roles and don't reflect the current engineering and product hiring wave.
For a candidate negotiating today, the posted ranges on live requisitions are the most actionable anchor.
| Role | Location | Posted Salary Band (Total Cash) | Source |
|---|---|---|---|
| Sr. Product Manager | South San Francisco | $185,000 – $240,000 | Zero G Talent board |
| Sr. Software Engineer, Backend | South San Francisco | $180,000 – $230,000 | Zero G Talent board |
| Sr. Machine Learning Engineer | Remote (US) | $175,000 – $230,000 | Zero G Talent board |
| Sr. Technical Program Manager | South San Francisco | $160,000 – $220,000 | Zero G Talent board |
| Sr. Software Engineer, DevOps | San Francisco | $180,000 – $220,000 | Zero G Talent board |
| Sales Director | Remote (US) | $150,000 – $185,000 | Zero G Talent board |
| Chief of Staff | (not on board) | $200,000 – $235,000 | Hireoven (13 postings) |
| Software Engineering Manager | (not on board) | $249,000 median | Levels.fyi |
| Product Manager (CRA level) | (not on board) | $288,550 top end | Levels.fyi |
| Solution Architect | (not on board) | $128,520 low end | Levels.fyi |
Equity follows a standard four-year vest: 25 percent at the one-year cliff, then monthly (2.08 percent per month) for years two through four, per Levels.fyi's breakdown of AKASA grants. The company does not publish refresh cadence, but industry practice at this stage (Series C, roughly 240 employees) is annual or biennial refreshers tied to performance and retention risk. Candidates should ask directly, as refresh policies are rarely in offer letters.
Benefits are spelled out on AKASA's careers page and corroborated by employee reports on Glassdoor and Built In Colorado: unlimited PTO, 100 percent employer-paid healthcare options (at least one plan tier), and employer contributions to health spending accounts (HSA/FSA). No public detail on 401(k) match, parental leave duration, or education stipends; ask in the recruiter screen.
The package is competitive for a 240-person Bay Area startup but not exceptional; the advantage is in the equity upside if the revenue cycle automation thesis pays off.
Inside the Interview Loop
The compensation tier and role mix, heavy on staff-plus ICs and first-line leads, signals a late-stage, product-driven organization that expects candidates to own outcomes from day one.
Public interview data specific to this AKASA (the healthcare AI automation company, not the Indian carrier) is thin. Glassdoor lists 28 interview reviews and 26 questions under the AKASA employer page, but detailed round-by-round breakdowns aren't published in available sources. Candidates who treat the process as a project, with artifacts, timelines, and rehearsal, outperform those who only wait for HR to email.
What Recruiters Screen For
- Keyword-to-reality match. The ATS pass is real. Mirror the req's must-haves honestly, then verify with an ATS checker.
- Defensible project stories. Two STAR narratives ready in 90 seconds each: one impact, one conflict or failure turned to learning.
- Mission specificity. "Why AKASA?" answers that cite the business unit (prior auth automation, claims processing) and the healthcare revenue-cycle problem beat generic brand praise.
- Logistics clarity. Notice period, preferred base (South San Francisco vs. remote), shift or travel willingness confirmed before the final round.
Strong Application Signals
- One tailored résumé per role family, not one generic upload across ten reqs.
- A spreadsheet tracking req link, apply date, recruiter name, and next expected stage.
- Timed mock completed at least once before the skills gate (ClavePrep or peer).
- A thoughtful question for each interviewer: "What's the hardest problem the team is actively solving right now?" or "How does this team work with adjacent orgs inside AKASA?"
Common Disqualifiers
- Treating every AKASA req as the same process, senior/staff language usually means fewer OAs and deeper ownership panels.
- Skipping the skills gate because "I'll wing the interview."
- Memorizing company trivia instead of rehearsing spoken problem-solving.
- Walking into HR without notice-period and location constraints ready.
- No timed practice, large-employer loops punish slow, unstructured answers.
Green, Yellow, and Red Flags in the Process
| Signal | What It Looks Like |
|---|---|
| Green | Clear stage list from recruiter, predictable follow-ups, written confirmation of next steps, interviewers who've read your résumé |
| Yellow | Long silence after a strong round without a stated SLA, last-minute panel changes, conflicting descriptions of role level |
| Red | Unpaid "trial work" that looks like free consulting, pressure to resign before a written offer, refusal to state whether the req is still funded |
Questions Worth Asking Recruiters
- What are the remaining stages for this req, and who owns each stage?
- Is there an OA, take-home, or live skills round for this track?
- Typical calendar time from this stage to offer for similar roles?
- Any hard constraints on location, shifts, travel, or start date I should know now?
- How should I prepare differently for campus vs. lateral loops?
Closing the Loop After Each Round
Within 24 hours: write down questions you missed and drill those patterns once; update STAR stories if an interviewer probed a gap; confirm the next stage and SLA with the recruiter; keep parallel prep warm via peer funnels so one delayed AKASA loop doesn't freeze your week. If the role closes, recycle practice, not the same generic résumé, into the next target.
The board data confirms AKASA pays at the top of the healthcare AI market and hires for ownership-heavy senior roles. The interview loop, while not fully documented in public sources, follows the established pattern for this tier: fundamentals gate → skills gate → ownership panel → offer hygiene. Candidates who map the funnel, drill the skills gate under time pressure, and bring two crisp STAR stories plus a mission-specific "why us" answer position themselves in the top decile.
Where the Work Gets Done
AKASA's physical footprint reflects a company built for distributed collaboration from day one. The headquarters sits at 400 Oyster Point Boulevard, Suite 222, in South San Francisco — a life-sciences corridor bordering the Bay that puts the team walking distance from Genentech, Amgen, and the UCSF Mission Bay campus.
BuiltIn lists the company at 110 total employees with 48 in product and technology, and the first-party board data shows five of six recent salaried postings anchored to this location: Senior Product Manager, Senior Backend Engineer, Senior Technical Program Manager, Senior DevOps Engineer, and a Sales Director role tagged to San Francisco proper.
Two satellite hubs extend the in-person option without mandating relocation. The Denver hub sits at 80206 (the Cherry Creek and Congress Park corridor), and the New York hub at 10010, placing it in the Flatiron and Union Square West neighborhood.
Both addresses appear on BuiltIn's office-location page alongside the HQ, and the company's own careers page describes "hubs of AKASAns in the Bay Area, NYC, and Denver to name a few" with supported co-working days in each metro. Neither hub has a published headcount, but the board's single remote-eligible posting (Senior Machine Learning Engineer, tagged "Remote - United States") and the Sales Director role (also remote) suggest the hubs function as optional collaboration anchors rather than staffed satellites with dedicated leadership.
The hybrid policy is asymmetric by design. isremote.fyi's scrape of AKASA's open requisitions shows roughly 87 percent of roles require on-site presence while only 12 percent are remote-eligible — a ratio that matches the board's current mix of five South San Francisco and San Francisco postings versus two remote ones.
The company describes itself as "remote-friendly" and notes team members in 29 states, yet the same careers page states hybrid roles typically require "12% remote · 87% in-office." That phrasing implies a default of four days on-site for hub-based employees, with flexibility for appointments, caregiving, or focus work. Typical time on-site is not specified in public sources, and the company does not publish a formal return-to-office mandate; the built-in flexibility reads as a recruiting lever for senior talent who want Bay Area proximity without a five-day commute.
What the spaces enable is deliberate rather than expansive. The South San Francisco suite houses product, engineering, clinical operations, and go-to-market teams under one roof — critical for a company whose AI models train on proprietary payer-provider interaction data that cannot leave controlled environments.
Denver and New York provide whiteboard rooms, video-conference pods, and desk hotels for the twice-yearly all-hands offsites the company highlights as its primary in-person rhythm. There is no public mention of hardware labs, simulation rigs, or specialized compute clusters on-premises; heavy GPU workloads run in cloud accounts governed by the same security posture that applies to remote engineers. For a candidate, the takeaway is concrete: if you join in a core engineering, product, or clinical role, you will be expected at Oyster Point most weeks; if you join in a designated remote slot, the hubs exist for quarterly planning and offsite weeks, not daily commuting.
Who Stays and Advances
AKASA's employee sentiment has been climbing. As of September 2026, current and former employees rate culture and values at 4.2 out of 5 stars on Glassdoor, 14 percent above the benchmark for similar information-technology companies, and that score has risen 13 percent over the prior twelve months.
The recommend-to-a-friend figure sits at 78 percent on Glassdoor's U.S. portal. Work-life balance scores range from 4.1 to 4.3 depending on the same sources, and career-opportunity ratings land between 3.8 and 4.1. The trend line matters more than any single snapshot: sentiment is moving up.
What the reviews and the company's own materials describe, consistently, is a cluster of traits that show up in people who stay and advance. Collaborative and supportive behavior tops the list. BuiltIn's employer profile quotes AKASA leadership: employees recommend the company because of a "collaborative and supportive culture, meaningful and challenging work, flexibility, strong leadership, and competitive pay and benefits." That phrasing mirrors what appears in anonymous reviews — teammates who share context freely, jump into incidents without being asked, and treat cross-functional friction as a design problem rather than a territorial one.
Mission alignment is the second filter. Comparably data indicates that 100 percent of surveyed employees say the mission, vision, and values motivate them. The mission — automating healthcare revenue-cycle work with generative AI — is specific enough to act as a self-selection mechanism.
Candidates who have wrestled with clinical documentation improvement, coding denials, or prior-authorization workflows tend to ramp faster because they already speak the customer's language. An engineering leader who joined from Verily describes fundamental shifts in product, company, and engineering culture during their tenure; people who treat that volatility as a signal to lean in, not a reason to wait for stability, are the ones who shape the next shift.
The four core values, never named in the public snippets but operationalized in a twice-yearly awards ceremony at the company offsite, function as a behavioral contract.
BuiltIn notes that recognition happens through "formal programs, compensatory rewards, and everyday moments that make contributions visible across the company." The offsite awards tie recognition directly to those values. In practice, that means the system rewards the helper as much as the hero.
Technical depth, unsurprisingly, is table stakes for the engineering and product tracks. The first-party board data shows senior backend, DevOps, and machine-learning roles banded between $175,000 and $230,000 base, with a senior technical program manager at $160,000–$220,000. But the interview loop screens for demonstrated depth, not credential depth. A candidate who can walk through a production incident they owned (what broke, what they instrumented, what they changed) carries more weight than one who lists the same stack on a resume without the scar tissue.
Flexibility appears in two flavors. The role mix includes fully remote positions (senior ML engineer, sales director) alongside South San Francisco–anchored roles (product, backend, DevOps, TPM). Employees who thrive manage that hybrid reality without making location a status marker. They also manage product volatility: the revenue-cycle automation space moves fast, and the roadmap shifts when a payer changes a policy or a new model capability drops. People who treat ambiguity as a design constraint, not a blocker, ship.
Intellectual curiosity shows up in the hiring criteria for adjacent functions too. Sales directors and product managers are evaluated on their ability to map a hospital CFO's pain to a technical architecture decision. The program-management hires, represented in the current posting set, need enough fluency to challenge engineering estimates without second-guessing them.
The common thread: ask the next question before the meeting ends.
Work-life balance scores above 4.0 suggest the culture sustains pace without glorifying burnout. The "flexibility" cited in BuiltIn's summary is not unlimited PTO theater; it shows up in calendar norms and an offsite cadence that doubles as a reset rather than a sprint review. People who set their own boundaries and respect others' boundaries last.
The profile that emerges: technically credible, mission-motivated, default-collaborative, comfortable with ambiguity, and explicit about values. The $120 million round that rewrote the hiring map also set the bar. If that profile sounds like you, the interview loop is designed to let you prove it. If it doesn't, the screens will surface the mismatch before an offer lands.
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