Senior AI EngineerCompany: MyaiOne — https://www.myaione.com/ Reports to: Chief Technology Officer (product direction from CEO)

Location:
[Remote / Hybrid — TBD] Type: Full-time, early-stage startup About MyaiOneMyaiOne is an early-stage startup building the AI infrastructure that lets mid-market companies run software development and client relationships the way the best AI-native companies do. We ship three complementary products — MyaiOne for Development, which converts a company's existing (brownfield) or new (greenfield) software into a dedicated AI Software Factory called a Rig, and MyaiOne Studio, which replaces antiquated CRMs and impersonal bulk communication with trained, role-specific AI Assistants and a per-client AI Concierge. We also run our leadership-focused MyaiOne Business Operating System, which elevates AI to be a key intellectual property of the company and an acknowledged enablement system for staff. Three more major systems are in stealth mode today. All products are wrapped in our AI Adaptation Services, an expert-led offering that helps leadership teams adopt and run on the platform day to day. We are fully AI-enabled. We build our products inside our own Software Factory and run our operations on the same Business Operating System we sell. If you join, you'll use the tools you're building on the day you build them. The RoleAs a Senior AI Engineer, you will own one of our products end to end: writing the roadmap, building it inside our Software Factory, shipping it to production, and watching how it performs for real customers. You'll develop deep expertise in what "good" looks like and use AI to close the gap between what you know cold and what you need to learn rapid. This is a builder role, not a management role. You'll be the senior-most technical and product owner of a system, working with the CTO on execution and the CEO on macro product direction, and pulling in support as the roadmap demands. Like any startup role, the scope will shift as the company grows — you'll need to be comfortable defining your own work when nobody has defined it yet. Background
• Proficiency in modern spec-driven and test-driven AI development. Practical experience leveraging Spec-Driven Development frameworks (such as BMAD, SpecKit, OpenSpec, or comparable tools)



alongside Test-Driven Development practices, along with strong technical judgment on when to adopt these approaches over traditional SDLC methodologies.
• Classic engineering discipline. Deep understanding of Test-Driven Development and the full SDLC, applied with rigor even when AI does much of the implementation.
• Depth in classic full-stack development. You've built and shipped production systems across front end, back end, APIs, and databases.
• Familiarity with common frameworks. Modern web stacks such as TypeScript, React, Next.js, Node.js, and PostgreSQL. Headless CMS experience (e.g., Payload) is a plus. Cloud deployment, CI/CD, and observability practices for keeping production systems healthy.
• Familiarity with new agentic architectures. Multi-agent orchestration, tool use and protocols like MCP, and context and memory management. Evaluation methods for agent output, and where to put human review points in an automated pipeline.
• Real product care. You have experience or want to learn product frameworks to help you choose what to focus on building. We apply Pragmatic Institute and Silicon Valley Product Group (SVPG) frameworks in our approaches.
• Comfort learning in public. You use AI to augment yourself into frameworks and domains you don't yet know deeply — a skill you exercise daily, not a gap you hide.
• Applied AI experience — agent design, conversational products, inference infrastructure, or AI-driven development tooling — running in production for real users.
• A Builder's bias. You'd rather ship and iterate against real usage than polish a plan. Key Development Philosophy
• Own the roadmap with guidance from Product leadership. Turn your product's ideal customer profile and use cases into a prioritized roadmap.
• Build inside the Factory. Factories can create large scale systems. Big ideas are needed to leverage the power of a Factory.
• Talk to each others and to customers.



We work with companies that believe AI should enable people, not replace them. Video calls and occasional in-person meetings are part of our culture. Expect to talk regularly with customers and with others across the company.
• Enable synchronous work with trained AI Assistants. When people are working, their time should yield the most value it can. All staff train and maintain AI Assistants that can quickly answer teammates when you're not available — speeding up the team and reducing noise for you.
• Teach. Senior people produce written and video teaching content for customers and colleagues. It's one of the highest-value uses of your time.
• Run unbiased User Journey Testing. Test the way a real end user would, following disciplined usability-testing practice. You must be able to set aside your own technical view and accurately play the user, so you validate real experience rather than your own preferences.
• Own production quality. You're responsible for the quality, cost, and reliability of everything underneath your product, including the AI systems it depends on.
• Dogfood relentlessly. MyaiOne runs on its own products; internal deployments are your first testbed. We All Own Revenue ResponsibilitiesRevenue is shared across our leaders, led by our selling teams. Your part is making sure the customers who already use your product get real value from it.
• An entrepreneurial, startup-ready mindset. You've thrived where resources are tight, priorities move, and ownership is total. You treat the product like it's your company.
• Own customer usage. You're responsible for how existing customers actually use your product: whether they adopt it, get stuck, or drift away.
• Listen and fix. Treat customer feedback as your most important input, and close the loop by shipping fixes.
• Watch it in use. Sit with our own team as they use your product, and see where it helps and where it gets in the way.
• Build a core group of customers. Find a set of customers who care about your product and work with them directly. They're your first test of every new idea.
• Support the selling teams. Share what customers value so the pitch reflects what the product actually does well.

📌 Senior AI Engineer (India)
🏢 MyaiOne
📍 India