Chief Technology Officer - AI Products
Location: India - Remote (US time zone)
Hours: Significant overlap with U.S. business hours
Type: Full time, contract
Experience: 8+ years
Compensation: INR 55+ LPA
Summary
OvalBrick has been retained by a U.S.-based venture-backed startup to recruit a Chief Technology Officer (CTO).
The company is building AI-driven software products that help businesses automate complex workflows and make better decisions. We are looking for a technically strong CTO who can own the technology strategy while remaining deeply involved in building the product.
The CTO will work closely with other executive leaders to turn business problems into products, define the architecture, write production code, make key technology decisions, and build the engineering team as the company grows.
The candidate will be based in India and work remotely with a U.S.-based team. Significant overlap with U.S. business hours is required.
This is not a primarily managerial CTO position. The successful candidate should be comfortable moving between product decisions, system architecture, software development, AI engineering, customer discussions, and technical leadership. As the engineering organization grows, the role will progressively shift toward broader technical and organizational leadership.
Key Responsibilities
Own the company's technical strategy, architecture, engineering roadmap, and major technology decisions.
Design, build, and ship production software; remain hands-on with critical parts of the codebase.
Translate ambiguous business and customer problems into product requirements, technical specifications, and working systems.
Lead development of AI-enabled applications using LLMs, RAG, agents, APIs, data pipelines, and other appropriate AI/ML approaches.
Select models, frameworks, infrastructure, databases, and cloud services based on product requirements, reliability, cost, and speed of execution.
Establish standards for architecture, code quality, testing, security, observability, deployment, and system reliability.
Build evaluation and monitoring systems for AI outputs, including accuracy, latency, cost, and failure modes.
Partner with CEO, COO on product strategy, prioritization, and product-market fit.
Participate directly in customer conversations and translate real workflows and feedback into product decisions.
Recruit and lead engineers as the organization grows, while establishing a high-quality engineering culture.
Represent the technical function in investor, partner, customer, and due-diligence discussions.
Qualifications
8+ years of software engineering experience, including meaningful technical leadership responsibility.
Strong hands-on software development background and a demonstrated record of shipping production applications.
Experience as a CTO, Head/VP of Engineering, Principal Engineer, Chief Architect, or comparable technical leadership role.
Experience building products in startups or other environments requiring high ownership and rapid iteration.
Strong full-stack or backend engineering skills, preferably including TypeScript/JavaScript and/or Python, modern web frameworks, APIs, and relational databases.
Strong system architecture skills across cloud applications, distributed systems, data, scalability, security, and reliability.
Practical experience building production AI applications, including LLM APIs, RAG, agentic systems, model/tool orchestration, AI evaluation, or related architectures.
Hands-on experience integrating commercial and open-source LLMs through APIs and model gateways such as OpenAI, Anthropic, Google AI, AWS Bedrock, OpenRouter, or comparable platforms.
Experience with modern cloud infrastructure such as AWS, GCP, or Cloudflare, including containers and automated deployment.
Ability to evaluate technical trade-offs and choose simple, maintainable solutions rather than adding unnecessary architectural complexity.
Strong product judgment and ability to turn loosely defined requirements into software customers actually use.
Ability to communicate effectively with engineers, customers, founders, investors, and non-technical stakeholders.
Experience hiring, mentoring, or leading engineers.
Preferred Qualifications
Building B2B SaaS or enterprise AI products from MVP through production scale.
Fine-tuning LLMs or smaller language models, including dataset preparation, evaluation, and deployment.
Designing and deploying production agentic systems, including tool use, multi-step workflows, state/memory, guardrails, evaluation, and failure recovery.
Deploying or integrating open-source models, including model selection, inference, hosting, or use through platforms such as OpenRouter.
Vector search, embeddings, AI evaluation, or model-serving infrastructure.
Data-intensive or distributed systems.
Enterprise integrations and customer-facing technical work.
Fundraising or technical due diligence.
Mobile application development.
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