What This Article Covers and What It Doesn't
Terra API, a 25-person health-data infrastructure company founded in 2021 by Kyriakos Eleftheriou, is advertising five open roles simultaneously: Commercial Lead, Designer, Forward Deployed Engineer, Sales Strategist, and AI Engineer, across engineering, sales, and design. The postings appear on the company's careers page and Work at a Startup, signaling a deliberate expansion of roughly one-fifth of the team. This article maps the screening criteria Terra uses right now, what its open roles reveal about team priorities, and how applicants are adapting. It does not cover Terra's product roadmap, funding history, or internal culture beyond what the hiring process itself reveals.
The boundary matters because the health-data API layer is tightening. Terra sits between wearable manufacturers, electronic health record systems, and the developers building AI agents that need normalized biomarker streams. The company's Y Combinator backing (W21) and San Francisco base put it in direct competition for engineers who have built production API integrations at scale, speak health data fluently, and operate at a velocity that makes typical startup pace look slow. When Terra opens five roles at once, the signal ripples: understanding Terra's specific filters becomes a proxy for understanding the segment's bar.
What this section excludes is deliberate. Terra's pitch deck, its Series A terms, its integration roadmap for new wearable APIs — none of those appear in the interview loop. Glassdoor reviews from 2014 describe a different company entirely (Terra Technology, Norwalk, CT), and while they illustrate how long a drawn-out process can feel, they don't reflect the current operation. A general hiring-process walkthrough on YouTube outlines a pre-interview phase where recruiters and hiring managers assess minimum qualifications before any candidate speaks to an engineer, followed by an interview phase that "may be repeated as many times as needed," typically two to four rounds across one to two months. That structure, not the company's mission statement, determines who advances.
The Screening Gauntlet: Stages and Filters
The clearest window into Terra API's hiring funnel comes from a single Glassdoor review posted by a candidate who interviewed at the company's San Francisco office. That account describes a four-stage process: an online coding assessment, a recorded interview, a cultural-fit discussion, and a final in-person coding round. No other first-hand reports for Terra API's current process appear in the available sources; the remaining interview write-ups describe Terra Technology (Pune) or HashiCorp's Terraform tool, which are different entities entirely.
The online assessment functions as the initial filter. The San Francisco reviewer said it evaluates problem-solving skills in a controlled environment before any human interaction. Candidates who clear that hurdle move to a recorded interview, an asynchronous step where responses are captured on video for later review by the hiring team. This stage lets Terra screen for communication clarity and baseline technical articulation without scheduling live slots for every applicant.
The third stage, labeled a "cultural fit discussion," signals that Terra weighs team alignment explicitly, not as an afterthought. The reviewer's wording, "assess technical expertise and team compatibility," implies a collaborative exercise rather than a pure algorithmic gauntlet. The research contains no breakdown of languages allowed, time limits, or evaluation criteria for this round.
Outside that single account, the research offers no Terra API–specific data on resume-screen keywords, take-home assignments, reference-check timing, or offer-stage negotiations. General Terraform-hiring discussions on Reddit and YouTube, covering state-file storage questions, HCL live-coding tests, and system-design trade-offs between REST and gRPC, reflect patterns at infrastructure-tool companies, not at Terra API. They cannot be mapped onto this employer without verification.
What the available evidence does support is a funnel that front-loads automated technical screening, inserts a recorded behavioral layer, then tests culture before a culminating live coding session. Candidates should prepare for each gate on its own terms: algorithmic fluency for the assessment, concise storytelling for the recording, values alignment for the culture chat, and production-grade coding hygiene for the onsite. The average 21-day timeline Glassdoor reports also suggests Terra moves quickly once a candidate enters the pipeline, a detail worth factoring into offer-timing decisions.
Five Roles, One Strategic Map
Terra's five open positions read like a strategic map of where a 25-person infrastructure company is placing its next bets. The roles cluster around three priorities: hardening the enterprise sales motion, deepening technical deployment capacity with strategic accounts, and building the AI ingestion layer the company says "the biggest AI labs use to access health data."
| Role | Location | Cash Compensation | Equity | Experience |
|---|---|---|---|---|
| Commercial Lead | London | £70K–£120K | — | 3+ years |
| Designer | London | £38K–£90K | 0.10%–0.50% | 3+ years |
| Forward Deployed Engineer | London / Cyprus / Remote US | $100K–$180K | 0.01%–0.15% | 3+ years |
| Sales Strategist | London | £50K–£90K | 0.10%–0.20% | 3+ years |
| AI Engineer | London | $50K–$120K | 0.10%–0.50% | Any (new grads ok) |
The two sales-adjacent roles — Commercial Lead and Sales Strategist — signal a deliberate shift from founder-led selling to a structured commercial engine. The Commercial Lead's £70K–£120K band sits well above the Sales Strategist's £50K–£90K; the careers page notes the team "closed our biggest Fortune 500 customer in 6 weeks." Both require three-plus years, ruling out junior hires.
The Forward Deployed Engineer is the most revealing role. The job description makes explicit what "forward deployed" means at Terra: "You are the technical bridge between Terra's platform and our highest-value customers… This is not support. This is not consulting. You are an engineer who ships — the difference is that what you ship lives inside the customer's stack, powered by ours." The role owns 3–5 strategic accounts simultaneously, designs integration architectures, writes production code in customer environments (webhook consumers, data transformation layers, retry logic), and debugs across the full stack, from a Garmin watch failing to sync to a customer's pipeline dropping events. Critically, the engineer translates field learnings back into product: "when you see three customers struggling with the same edge case in sleep data normalization, you don't just fix it for them; you work with our engineering team to fix it in the platform."
The listed customer scenarios confirm the verticals: an AI lab ingesting continuous heart rate, HRV, and sleep stages from 200,000-plus users across multiple brands; an insurer using real-time biometrics for dynamic premium pricing; a clinical research platform running a 10,000-participant longitudinal study across Fitbit, Garmin, and Apple Health; a fitness platform migrating off 15 separate wearable integrations; a wearable manufacturer becoming a data supplier on Terra's platform.
The AI Engineer role, notably open to new graduates, signals Terra is building a dedicated AI integration layer; the posting mentions "multiple AI products, such as OdinAI, Graph API, and many more." The equity range (0.10%–0.50%) matches the Designer's, higher than the Forward Deployed Engineer's (0.01%–0.15%). The Designer's wide cash band (£38K–£90K) implies the role spans individual contribution to design leadership, likely owning developer experience, dashboarding, and the visual language of a product that "gives companies a single way to connect to health data, normalize it, stream it, analyze it, and build products on top of it."
The concentration in London (four of five roles) with a Cyprus/US remote option for the Forward Deployed Engineer reflects the company's primary hub (LinkedIn lists London as headquarters) and its need for time-zone coverage near strategic US accounts. The message is coherent: Terra is investing in the go-to-market and deployment muscle required to serve enterprise and AI-lab customers at 30-billion-events-per-year scale.
Skill Signals: What Terra Actually Looks For
The job postings read less like wish lists and more like a filter designed to reject anyone who hasn't lived the specific pain Terra solves. Across the five open roles, the requirements converge on a narrow profile: engineers who have built and maintained the profile described above.
The Integration Core
For the Forward Deployed Engineer role, the most detailed listing, Terra demands three-plus years building software with direct experience designing and consuming REST APIs at scale. Candidates must have owned integrations end-to-end: OAuth 2.0 and API key auth flows, webhook architectures, error handling, retry logic, idempotency. They need to prototype a webhook consumer, build an SDK wrapper, or debug a customer's data pipeline in the same afternoon using Python or JavaScript/TypeScript. The Backend Developer listing mirrors this: understanding of RESTful APIs, database design, and server-side programming. The AI Engineer posting adds Go and Java to the language mix. This is a filter for people who have wrestled with the specific failure modes of third-party data ingestion: rate limits, schema drift, partial outages, backfill nightmares.
Health Data Fluency as Table Stakes
Terra doesn't treat health domain knowledge as a "nice to have." The Forward Deployed Engineer listing explicitly requires experience with health, fitness, or biomedical data, knowing what HRV is, why sleep staging is hard, and what makes wearable data noisy. Familiarity with HIPAA, GDPR, FHIR, and HL7 is listed as a qualification. Candidates who have worked at or with companies in wearables, digital health, or health AI get flagged. The signal is clear: Terra cannot afford to teach the domain. The infrastructure layer sits between hundreds of siloed sources — wearables, sensors, medical devices, blood tests, clinical platforms — each with its own authentication, permissions, schema, latency, and reliability problems.
Velocity and Autonomy as Explicit Filters
The careers page states it plainly: "Terra moves at 200 km/hr. This is not a regular 9-5 job. Don't apply if you can't keep up." The "must haves" list reads like a stress test: must be fast, must be relentless, must work autonomously, must want to work hard. "If you like long process documents and planning meetings, you'll hate it here." The Forward Deployed Engineer role requires context-switching between five different customer architectures in a week without losing depth on any. Terra's team of 25 ships in days, not months, and the "No Lanes" principle means your title is a rough guess at what you'll actually do. The screening looks for evidence you've operated in this mode before: shipping without approval layers, fixing problems you spotted without escalation paths, working in the open where everyone sees your work (good and bad).
Translation Layer: Technical to Commercial
The Forward Deployed Engineer sits at the intersection of engineering and revenue. The listing requires communicating clearly with both engineering teams and non-technical stakeholders: executives, product managers, compliance teams. You translate "our data looks wrong" into a root cause and a fix. When three customers struggle, they address it in the platform. You build reference implementations, SDKs, and sample apps that make Terra's API easier for every developer. This dual fluency — deep technical credibility plus the ability to navigate procurement, compliance, and product strategy conversations — is what separates a forward-deployed engineer from a support engineer. The Sales Strategist role similarly prefers enterprise sales experience in health tech, signaling that Terra's commercial motion is technical consultative selling.
The Athlete Signal
"Big plus: You are an athlete, or care about quantifying your data" appears in the AI Engineer posting and gets expanded in the Forward Deployed Engineer listing: "You are an athlete. You train, you compete, you push limits, or at the very least, you are obsessed with quantifying your own data. The discipline, ambition, and courage it takes to show up every day and get better is the same energy we run on. If you understand the data because you live it, you'll build a better product." Terra's product is the infrastructure for quantified-self data. An engineer who has never stared at their own HRV trends, wondered why their recovery score dropped, or debugged a missing sleep stage in their Oura ring will build the wrong abstractions. The screen selects for people who are the user.
Design and AI Specialization
The Designer role calls for hybrid UX/UI expertise turning complex workflows into simple, elegant experiences, with the implicit requirement of understanding backend development concepts. The AI Engineer posting mentions building the aforementioned products and prefers STEM degrees with growth marketing and product development experience. Both signal Terra is productizing its data layer into higher-level intelligence tools, not just piping raw streams.
Candidate Strategies: How to Stand Out
Terra's job postings read less like requirements lists and more like filters for a specific mindset. The company states plainly: it hires people who "get things done, think from first principles, and learn ferociously."
The Video Strategist listing, the most detailed of the five open roles, makes the portfolio bar explicit: "You have a portfolio of work that stopped people mid-scroll. Not corporate sizzle reels. Actual short-form content that performed: views, shares, saves, comments. You can point to specific pieces and tell us why they worked."
The company's own onboarding practice reinforces what it values: "Turn new hires into super users; having new hires at Terra go through an onboarding process as first-time users gives us an ultra-high resolution of our product journey."
Domain fluency matters more than credentials. The Video Strategist posting demands candidates who "understand health, fitness, and performance culture. Not because you studied it — because you live in it. You know why a clip of someone talking about HRV at 3 a.m. after a hard training block hits differently than a generic wellness quote."
Contrarian thinking appears repeatedly: "You have a contrarian eye. You don't copy what's trending. You look at what everyone else is doing and find the angle they missed." The podcast describes "stalking your most important user" by studying call transcripts, emails, and social media to understand a single user in depth, and explicitly warns: "never ask your users about opinions... those answers are super vague, and they're not grounded in any facts."
Technical sharpness with the toolchain is table stakes, but the posting clarifies: "Premiere, Final Cut, DaVinci, After Effects, CapCut, whatever. The tool doesn't matter. What matters is you can take raw footage with bad audio and inconsistent framing and turn it into something that looks and sounds intentional."
Opinionated execution rounds out the profile: "You are opinionated about content. You have strong views on what makes a good hook, what makes a good cut, what makes someone hit share. You argue for your edits. You don't just take notes and execute — you push back when the edit would be worse."
Referrals remain a quiet accelerator. Terra's investor roster, including Y Combinator (W21), General Catalyst, Samsung NEXT, and NEXT Ventures, creates a traceable network.
The final filter: "proof of excellence: a lot of followers in social media, or posts with millions of users, with a formula you recreate often." That metric applies narrowly to the content role, but the underlying principle scales. Repeatable impact, documented and explained, beats potential every time.
The Ripple Effect: What Terra's Hiring Means for Frontier-Tech Talent
Terra API's five open roles are not an isolated hiring sprint. They are a leading indicator of a structural shift in how health data moves, who controls the pipes, and what talent commands a premium. The company sits at the intersection of three converging forces: a healthcare labor market propping up the entire U.S. economy, an AI adoption curve that has made health systems the fastest-moving buyers in enterprise software, and a talent pool pulled simultaneously by Big Tech, incumbent EHR vendors, and a new wave of AI-native startups.
Healthcare jobs accounted for 43 percent of all U.S. job growth in the first half of 2025. Without the sector, the economy would have shed roughly 85,000 jobs over the same period. Employment in health care and social assistance has risen in every month since January 2022, adding 695,000 roles through November 2025 alone. Meanwhile, professional and business services, the traditional landing zone for API and integration engineers, lost 57,000 jobs in January 2026. Private employers outside health care added just 22,000 positions that month. The labor market is bifurcating: health care is hiring; the rest of tech is freezing.
Health systems now supply $1 billion of the $1.4 billion flowing into healthcare AI, 75 percent of the total, and they have shortened buying cycles from eight months to 6.6 months. Outpatient providers move faster still, cutting cycles to 4.7 months. That purchasing velocity creates immediate demand for the plumbing that connects models to clinical workflows. Terra's API layer — wearable data, lab results, EHR reads and writes — is exactly that plumbing.
Menlo Ventures reports that startups capture 85 percent of generative AI spend in healthcare. The incumbents, Epic, Oracle Health, and athenahealth, are bolting on ambient scribes and coding automation, but their architectures are monolithic. Terra's pitch is composability. That pitch requires engineers who understand FHIR, HL7, and the reality of sandbox environments that never quite match production.
The talent arithmetic is unforgiving. JobsPikr data shows healthcare tech roles up over 30 percent year-over-year. Postings for health data engineers, EHR analysts, and clinical informatics managers rose 32 percent in the last 12 months. Nurse practitioner roles climbed 40 percent in 18 months. The same pool of engineers who can build secure, auditable data pipelines is being courted by health systems building internal AI stacks, by payers automating prior authorization (up 10x year-over-year), and by pharma companies fine-tuning foundation models for drug discovery (two-thirds of pharma firms now building or fine-tuning proprietary models).
Compensation is adjusting. Real wages in healthcare have grown at 1.5 percent annually versus 0.8 percent for the overall economy. Stripe's Machine Learning Engineer posting shows $212K–$318K; according to ASML's Principal Opto-Mechanical Engineer posting, principal engineers sit at $177K–$265K. Health-data API roles with compliance expertise, such as HIPAA, GDPR, FHIR, and HL7, command a premium over generalist backend work because the cost of a breach is existential.
The ripple extends beyond salary. Terra's hiring signals that the "digital health" category, projected at $54 billion revenue in 2025, reaching $70 billion by 2029, has moved from pilot budgets to line items. Health systems are no longer experimenting; they are deploying. Kaiser Permanente rolled Abridge's ambient documentation across 40 hospitals and 600-plus offices in the largest generative AI deployment in healthcare history. Advocate Health evaluated 225 AI solutions and put 40 into production. SimonMed scaled from fewer than 10 vendor partnerships to more than 50. Each deployment needs data ingress and egress. Each needs the API layer Terra sells.
For candidates, the implication is clear: the half-life of relevant knowledge has shrunk to months. Deloitte notes that AI knowledge half-life is now measured in months, not years. The engineers who advance past Terra's screen will be those who treat the API not as a static contract but as a surface that evolves with every new model capability: voice interfaces for patient engagement, automated prior authorization, real-time clinical decision support. The five open roles are a bet that the next wave of healthcare value accrues to the layer that makes data liquid, compliant, and model-ready. The market is voting with its wallet. The talent that follows the liquidity will set the pace for the next decade.
The screen doesn't care about your resume. It cares about what you've shipped.
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