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Salary
$39k – $96k per year (Estimated)
Location
In office (Delhi)
Seniority
Staff

Confirmed on the employer's own hiring board on Sep 23, 2026. First seen by Alion on Sep 8, 2026. Xponentiate scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Founded in 2022 out of a venture studio, Xponentiate is a specialized recruitment and talent acquisition firm dedicated exclusively to the healthcare sector. The company provides tailored hiring solutions to build C-suite leadership, technical, clinical, and operational teams for digital health, medtech, and pharmaceutical organizations globally. By leveraging deep industry network insights, it connects health-tech startups and enterprise healthcare clients with vetted professionals to accelerate organizational growth.

About the Company

Health Arx Technologies is the parent company behind two consumer health brands: BeatO, a connected diabetes care platform delivering glucometers, CGM, and a smart scale alongside app-based coaching and an in-house doctor network, and Metaboliq, its GLP-1-led weight and health management services brand. Both brands run e-commerce operations and sit on shared data and cloud infrastructure, with technology functioning as the operating system that product, operations, sales, clinical, and support teams all run on.

Requirements

Role Summary

This is a builder-leader mandate spanning engineering, product, data, infrastructure, and AI systems, not a pure engineering-management role. The primary measure of success is unlocking capability for business and operations teams and driving business outcomes directly, rather than managing a roadmap from a distance. Within six months, the person in this seat should be operating independently as the leadership team's single point of accountability for technology delivery, working directly with the CEO without needing day-to-day direction. The final level, Sr. Manager or Director, will be set based on the strength of the candidate rather than fixed in advance.

Key Responsibilities

  • Engineering leadership. Lead and level up an existing shared engineering team of 15-20 across app (Android/iOS), web, backend, and QC, working across multiple concurrent projects.
  • Product ownership. Operate with a product mindset: translate business problems into specs, make scope trade-offs, and own outcomes rather than tickets, partnering directly with founders and functional leaders.
  • Data. Co-own analytics pipelines, event instrumentation, dashboards, and the data-driven decision loop for product and operations, working in a GCP/BigQuery environment alongside the Analytics and Data Engineering team.
  • Infrastructure. Own cloud architecture, cost, reliability, and security on Google Cloud (Cloud Run, Cloud SQL, Pub/Sub, Firebase).
  • Ops enablement. Build internal tools, automations, and AI agents that measurably speed up and improve sales, support, logistics, and clinical operations.
  • AI systems. Architect and ship LLM-powered products end to end, including WhatsApp-first conversational agents, document intelligence, voice agents, and internal automation agents.

Requirements (Must-Haves)

  • Recent hands-on coding. Has personally shipped production code within the last 12 months. This is non-negotiable; the role requires prototyping, reviewing, and unblocking at the code level.
  • Full-spectrum builder. Has built and shipped technology for both consumer-facing audiences (mobile apps, web, commerce) and internal audiences (ops tools, dashboards, automations), and is deep in at least two of backend, app, web, data, and cloud, conversant in all.
  • AI-first in daily practice. Uses AI coding tools (Claude Code, Cursor, Copilot, or equivalent) as a default way of working, and can drive AI-assisted engineering practices across a team without sacrificing quality.
  • Has shipped AI products, not just experimented with them. Can design and deliver production LLM systems end to end: prompt/agent architecture, model selection and cost tiering, conversation orchestration, evaluation and safety, and integration with messaging channels and payments.
  • Solution mindset at pace. Bias to shipping working solutions quickly, paired with strong first- and second-order thinking that anticipates downstream effects and edge cases before they happen.
  • First-time-right discipline. A track record of low-regression delivery: testing rigor, careful rollouts, monitoring, and root-cause habits, so that speed does not come at the cost of breakage.
  • Data-driven. Instruments what they build and argues from numbers. SQL fluency is expected, with experience in product analytics (Firebase/GA4, BigQuery or similar) strongly preferred.
  • Independent operator with leadership. Comfortable taking a one-line problem statement from the CEO, structuring it independently, and shipping a solution, with sound judgment on when to check in versus when to just decide.

Preferred Qualifications

  • Healthtech or digital health experience, particularly at a direct or adjacent competitor: chronic care, diagnostics, connected devices, telehealth, or GLP-1/weight management programs.
  • Startup experience spanning both 0→1 (built something from nothing) and 1→10 (scaled a working product and team).
  • Experience with connected hardware or IoT device ecosystems, including BLE devices and device-cloud sync.
  • Experience with WhatsApp Business API, payment gateways (Razorpay), Shopify or e-commerce platforms, or contact-centre/IVR systems.
  • Experience running engineering against GCP cost and reliability constraints.
  • 7-12 years of experience overall, drawn from senior engineer, engineering manager, or founding engineer roles at Series A-C consumer startups, or from a founder/CTO background at a smaller startup seeking scale and stability.

Benefits

  • A mandate spanning product, engineering, data, infrastructure, and ops in one seat, with direct CEO and leadership access rarely available to Directors at larger companies.
  • Real scale and real stakes: a consumer health product used daily by a large chronic-care population, where decisions affect health outcomes, not just engagement metrics.
  • Genuine leadership appetite and budget to build LLM products and an AI-native engineering practice, rather than AI positioned as a bolt-on experiment.
  • A compressed path to a true head-of-technology mandate for a senior engineer or engineering manager ready to step up.
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