AI Lead (Hindi Speaking)

Owns the product roadmap across the platform and decides what gets built next, based on real usage rather than matching whatever competitors are advertising. Works closely with the team (the team responsible for product development for clients and Radix's internal processes) to translate their requirements into working, built solutions. Builds solutions for two parallel tracks: (a) internal tools and processes used by Radix teams on the floor, and (b) productized AI solutions delivered to existing clients and positioned for the broader market. Partners with account/client teams to ensure AI solutions built for internal use are successfully adapted and deployed for existing client accounts where relevant. Builds and maintains the multi-model routing layer and agentic tooling directly, especially in the early stage before there's a team to hand it to. Builds and maintains the scraping and data acquisition pipelines that feed the platform, sourcing from the open web, structuring it, and keeping it running as sites change and break things. Manages API keys and provider relationships across LLM platforms and data sources provisioning, rotation, cost tracking, and knowing when a provider needs to be swapped out. Sets the compliance bar (audit trail, humanin-the-loop, data residency) as a build requirement from day one, not something added later for a specific deal. Personally checks that anything described as source-cited or grounded actually is, before it reaches a client especially in banking or healthcare. Hires and grows the team as the platform Job Description Reporting No direct reports on day one this person is expected to build, and hire underneath themselves as the workload justifies it. Not responsible for day-to-day client account management or campaign execution. Job Requirements

Desired Candidate Profile

Multi-model systems 8+ years in software or AI product/engineering, at least 3 of those hands on with applied LLM systems. Has actually been on call for a multi provider system when something broke a provider updated a model and behavior drifted, output schemas stopped matching across providers, a primary provider went down and fallback logic had to kick in. Fixed it themselves, not just filed a ticket. Has owned or been directly accountable for an inference cost budget, not just aware that costs exist. 3+ years working hands-on with agentic or tool calling setups (MCP or similar), has debugged a broken agent step or a failed tool call personally. Data acquisition and scraping Can build and maintain scrapers against sites that don't want to be scraped handling rate limits, rotating proxies/headers, structural changes that break selectors, and the general maintenance burden of scraping at all. Understands the legal and compliance edges here robots.txt, ToS, copyright, and what changes when personal data is involved (this matters more in the GCC given PDPL/SDAIA), and knows when to flag something rather than just building it. Has built a data pipeline end to end: scrape or pull from an API, clean it, store it, and get it into a form the product actually uses , not just a one-off script that ran once.Product ownership 10+ years total in product, including 4+ years at Head of Product, VP Product or CPO level. Has taken an AI product from nothing to real paying customers or enterprise logos not a prototype, not an internal tool. 5+ years selling into or building for enterprise buyers, long sales cycles, procurement, security review. Consumer or SMB backgrounds don't map well here. Has run a multi product portfolio (5+ live products) on shared infrastructure and knows how to say no to half of it. Compliance and grounding 5+ years working inside enterprise compliance constraints, audit logs, human-in-the-loop approval Employment Type Full-time