About Company
Moative is an AI diffusion company. We partner with midmarket companies in asset-heavy, regulated industries to co-build deeply industry-specific agentic and machine learning solutions, which then get diffused across the industry through revenue-share and equity-linked models. Our Past: We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs. Team: Our team of 20+ employees consists of data scientists, AI/ML Engineers, and mathematicians from top engineering and research institutes such as IITs, CERN, IISc, UZH. Our team includes academicians, IBM Research Fellows, and former founders. This role leads technology for our healthcare business, working alongside forward-deployed engineers, data scientists and revenue cycle operators to build an AI management services organization (AI MSO) for US healthcare practices.
Work you’ll do
We are building an AI management services organization (AI MSO) for US healthcare practices. We combine operational expertise, data infrastructure and AI to manage and improve revenue cycle and administrative workflows. We automate suitable tasks progressively, with clear controls and human accountability for exceptions and consequential decisions.
As CTO, you will own the technology strategy, platform architecture and engineering organization behind this business. You will work with our founders, practice owners and billing leaders to decide what to build, which workflows to prioritize and how to measure results. You will remain hands-on in architecture, prototypes, code reviews and difficult production problems.
You will build a reusable platform that connects practice systems, supports reliable automation and captures operational learning across engagements, while maintaining appropriate separation of each practice’s data. The work includes payer-portal agents, voice-based payer follow-up, claim-journey analysis, denial management and payment-posting workflows.
Technical leads will own day-to-day pod delivery within the direction you set. You will resolve major technical trade-offs, develop those leaders and remain accountable for platform quality, reliability and technical risk.
Responsibilities
Own technology strategy, platform architecture and engineering standards for the healthcare AI MSO.
Work with founders, practice owners and billing leaders to assess workflows, establish baselines and prioritize investments by business value, feasibility and dependencies.
Lead product and platform decisions, balancing practice-specific requirements with capabilities that can be reused across customers and specialties.
Design solutions across EHRs, practice-management systems, clearinghouses and payer portals, connecting data pipelines, AI agents and operator workflows.
Define the practice data architecture, integrating claims, remittances, EOBs, denial codes and operational records into validated, traceable data with clear access controls and isolation between practices.
Separate operational data that requires patient identifiers from de-identified analytical datasets, and define approved uses of each.
Stay hands-on through architecture and code reviews, targeted prototypes and resolution of complex production issues.
Make build-versus-buy, vendor and model decisions based on reliability, security, cost and business value.
Establish technical controls for healthcare privacy, security and compliance, working with legal, compliance and client stakeholders on approved data flows, retention, vendor access and incident response.
Set production evaluation and release criteria, including monitoring, human escalation, recovery procedures and ownership of failures.
Own engineering and infrastructure budgets, platform operating costs and investment in reusable capabilities.
Hire, develop and retain engineers, data scientists and technical leads, with clear accountability for quality and delivery.
Represent Moative’s technology with practice owners, partners and investors, explaining technical choices and their implications for practice economics.
Who you are
You are a technology leader who has built products and remains close to engineering. You can decide what to build with a practice owner, examine an architecture with an engineer and explain investment choices to an executive or investor.
You have worked with fragmented operational systems, inconsistent data and workflows that depend on people’s judgment. You investigate how work is actually done before deciding what to automate, and you understand that reliable data and clear processes are foundations for useful AI.
You have built and scaled products or a technology business, made decisions with incomplete information and stayed accountable for customer adoption and commercial outcomes. You can develop strong technical leaders while stepping into difficult engineering problems when needed.
You want to build the technology foundation of an AI MSO and take responsibility for how it performs as the business grows.
Skills & Requirements
Must have
At least 15 years of relevant engineering and technology leadership experience, with recent hands-on involvement in architecture, solution design, prototyping and production troubleshooting.
Experience building and scaling a product or technology business in a founding, CTO or senior engineering leadership role, with clear evidence of customer adoption, commercial outcomes and your own contribution.
Experience owning product and technology decisions from customer discovery through production, adoption and ongoing improvement.
Deep experience integrating, cleaning and modeling fragmented operational data, including building reusable platforms serving multiple customers with clear data isolation and access boundaries.
Experience leading teams that deploy and support AI in live operations, including LLM-based applications or agents, with evaluation, monitoring and human escalation.
Strong Python, SQL and cloud architecture skills across at least one platform—AWS, Azure or GCP—with the ability to review code, challenge designs and build prototypes.
Experience delivering healthcare or RCM products, with practical understanding of billing workflows, claim submission, payer interactions, denials, appeals and payment posting.
Experience establishing technical controls for sensitive healthcare data, including access management, audit trails, secure logging, vendor access and incident response.
Experience building engineering and data teams, hiring senior technical leaders and establishing engineering standards.
Experience owning technology budgets, vendor decisions and operating costs, and explaining investment trade-offs in business terms.
Experience working directly with CXOs, founders and investors to agree priorities, resolve conflicting expectations and communicate technical risk.
Ability to demonstrate a product you chose to build, the architecture and team you developed, the trade-offs you made and the results achieved.
Preferred experience
Experience building for US outpatient practices, MSOs or RCM companies, including working with US billing teams and payer workflows.
Experience taking a company through an acquisition, merger or other successful exit, including technical diligence and transition responsibilities.
Experience turning services engagements or client-specific solutions into reusable products and platforms.
Experience with healthcare data exchange and integrations involving claims, remittances, EHRs, practice-management systems or clearinghouses.
Experience with process mining, operational knowledge systems or adapting smaller models for domain-specific tasks.
Experience building browser automation or voice agents for operational workflows.
Location: Chennai or Bangalore. Chennai preferred. This role involves regular in-person collaboration with our founders and the healthcare AI pod.
Working at Moative
Moative is a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, efficiency and high-quality outcomes. We believe the future of work is AI-augmented and boundaryless. Here are some of our guiding principles:
Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast – measured in hours and days, not weeks and months.
Own the canvas. Throw yourself in to build, fix or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you don’t need a person with the highest title to say that out loud.
High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We don’t like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.
If this role and our work is of interest to you, please apply. When applying, describe a product or platform you built and scaled, ideally in healthcare or another data-intensive, regulated industry. Explain the customer problem, your product and architecture decisions, the team you developed, the hardest technical or data challenge, and the commercial or operational results. Include any founding or exit experience and your specific contribution. Share only material you are authorized to disclose; anonymized descriptions are sufficient.