Founding Staff Engineer

Accountabilities:

End-to-End Product Engineering: Own the design, development, deployment, and ongoing improvement of the entire consumer product, from database architecture and backend services to frontend interfaces and reader-facing experiences.
Production Infrastructure and Reliability: Build and operate the production systems supporting interactive storytelling, including data models, streaming responses, background jobs, concurrency management, payment processing, credit ledgers, deployment pipelines, and observability.
AI-Powered Storytelling: Design and improve AI-driven experiences that enable users to interact with fictional characters, influence storylines, and maintain coherent narratives across hundreds of conversational turns.
Memory and Context Management: Develop strategies for persistent story memory, contextual retrieval, character-specific knowledge, relationship tracking, and event continuity to ensure that previous interactions meaningfully influence future story developments.
Model Selection and Orchestration: Evaluate and integrate large language models for different tasks, optimizing model selection, orchestration, inference costs, and response latency while maintaining narrative quality.
Evaluation Frameworks and Benchmarking: Build practical benchmarks, test cases, and evaluation systems to measure narrative consistency, character behavior, contextual accuracy, user experience, and potential failure modes.
Experimentation and Iteration: Design experiments before investing in custom infrastructure, test competing approaches quickly, analyze real-world user behavior, and use evidence to guide product and technical decisions.
AI Agent Integration: Use AI coding agents and development tools to accelerate implementation while maintaining control over architecture, code quality, system integrity, and long-term maintainability.
Technical Architecture and Standards: Establish foundational engineering practices, architectural patterns, documentation, and development standards that enable future engineers to contribute effectively as the team grows.
Data Integrity and Production Debugging: Ensure that individual story interactions and system events can be reconstructed and analyzed, making it possible to investigate failures, diagnose unexpected model behavior, and improve reliability.
Product Quality and User Experience: Maintain high standards across performance, responsiveness, typography, interface state, reliability, and narrative immersion to deliver a polished consumer product.
Technical Leadership: Work closely with the founders, product designer, and senior technical advisers to define priorities, challenge assumptions, make independent technical decisions, and align engineering execution with product strategy.
Strategic Technology Decisions: Evaluate whether to build, buy, or adapt existing tools and AI systems, selecting technologies based on measurable product value, scalability, implementation speed, and cost.
Future Team Development: Establish the technical foundation and engineering culture for future hires, with the opportunity to take on broader leadership responsibilities as the organization scales.
Requirements:
At least 5 years of relevant professional experience, with substantial hands-on expertise in production software engineering and the development of AI-powered applications.
Demonstrated experience building and operating production systems that use large language models (LLMs) as a core component, including diagnosing failures with real users and implementing effective solutions.
Strong backend engineering and system design capabilities, including database architecture, API design, concurrency, background processing, data integrity, and production reliability.
Experience developing and shipping consumer-facing products end to end, with an understanding of how technical decisions influence usability, engagement, retention, and overall product quality.
Strong knowledge of LLM integration, prompt and context management, memory architectures, retrieval strategies, and model orchestration.
Practical experience designing meaningful AI evaluations and benchmarks, with the ability to measure specific behaviors and failure modes rather than relying solely on generic evaluation scores.
Familiarity with AI coding agents and agent-assisted development workflows, including the ability to review generated code critically and identify architectural, security, and reliability risks.
Ability to design and execute rapid experiments, compare alternative approaches, interpret results, and make data-informed decisions before committing to complex infrastructure.
Strong understanding of production operations, including deployment, monitoring, observability, debugging, performance optimization, and system resilience.
Experience with modern web technologies, preferably TypeScript, Next.js, and PostgreSQL, along with familiarity with integrating frontier language models through APIs.
Understanding of payment systems, usage-based billing, credit accounting, streaming architectures, and asynchronous background processing is beneficial.
Strong product intuition and design sensibility, with an appreciation for the details that make consumer experiences intuitive, engaging, and enjoyable.
Ability to work independently in an early-stage environment, take ownership of ambiguous problems, and make sound decisions without relying on detailed specifications.
Excellent communication skills, including the ability to explain complex technical concepts in plain language and constructively challenge founders, advisers, and other stakeholders.
A collaborative, pragmatic mindset and willingness to balance rapid experimentation with maintainable architecture and reliable production systems.
Genuine curiosity about AI, interactive storytelling, user behavior, and the factors that encourage people to return to a product.
Interest in taking on broad technical ownership and progressing toward a Head of Engineering role as the team expands.
Experience as an early engineering hire at a startup and a strong technical education, such as from an IIT, NIT, IIIT, or BITS institution, are advantageous but not mandatory.
Benefits:
Competitive salary: Annual compensation ranging from ₹50,00,000 to ₹1,00,00,000, depending on experience and suitability for the role.
Fully remote work: Work from anywhere in India with the flexibility of a remote-first position.
Founding-level ownership: Take responsibility for the product's engineering foundation, architecture, technology choices, and long-term technical direction.
Direct founder collaboration: Work closely with experienced founders and a founding product designer, with access to senior technical advisers for guidance and strategic input.
Long-term business orientation: Join a business funded by its founders' existing proceeds, with no stated dependence on external fundraising timelines.
Significant technical autonomy: Influence the technology stack, evaluate emerging AI systems, and decide which capabilities to build internally or leverage through existing solutions.
AI-first development environment: Access AI coding tools, computing resources, and model budgets to support meaningful experimentation and accelerate product development.
Rapid experimentation culture: Test ideas, compare technical approaches, and iterate based on real user behavior rather than prolonged planning cycles.
Career progression: Opportunity to grow into a Head of Engineering position as the business and engineering team expand.
Broad professional impact: Shape a new AI-powered consumer product and establish engineering practices that future team members will inherit.
Healthcare, paid leave, and additional perks: Specific details regarding insurance, paid time off, bonuses, and other benefits have not been disclosed in the available job description and should be confirmed during the hiring process.