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AI-Native B2B SaaS

Technology Lead

Role Overview

We are looking for an exceptional Technology Lead with deep AI expertise to lead the technology development of an ambitious AI-powered B2B SaaS platform targeting global markets.

This will be the lead technology role from the startup’s beginning, with responsibility for establishing the technical foundation of the product and taking it from early development through launch and scale.

The Technology Lead must combine strong hands-on software engineering capabilities with advanced practical expertise in Artificial Intelligence. This is not a coordination-only or management role. The successful candidate should be capable of making key architecture decisions, building and reviewing critical components, selecting the appropriate AI technologies and models, and leading internal developers and external technology partners.

The role will work closely with the business and product leadership to translate the product vision into a scalable, secure, AI-native technology platform.

    • Own the overall technology architecture, engineering strategy and technical roadmap from the early stage of the company.

    • Lead the technical development of the product across AI, web, mobile, backend, APIs, databases, cloud infrastructure and integrations.

    • Define the appropriate AI architecture and determine where AI should be embedded within the product to create meaningful customer and operational value.

    • Design, develop and oversee AI-native product capabilities, including intelligent automation, AI agents, LLM-based functionality and other relevant AI technologies.

    • Evaluate and select appropriate AI models, frameworks, APIs and infrastructure, balancing capability, performance, scalability, security and cost.

    • Develop and manage integrations with leading AI models and platforms while determining where proprietary capabilities or specialized models should be developed.

    • Establish appropriate approaches for prompt engineering, model orchestration, RAG, AI agents, structured outputs, evaluation, monitoring and guardrails, where relevant to the product.

    • Translate business and product requirements into practical, scalable technical solutions.

    • Personally contribute to development and technical problem-solving where required, particularly during the early stages.

    • Lead and support internal developers and effectively manage external development partners and technology vendors.

    • Review code, architecture, technical designs and implementation quality.

    • Establish engineering standards covering development, testing, deployment, documentation, CI/CD and release management.

    • Oversee cloud infrastructure, databases, application hosting, cybersecurity, monitoring, reliability and performance.

    • Ensure the architecture can support multi-market, multilingual and scalable SaaS deployment.

    • Identify technical risks, dependencies, scalability constraints, AI-related risks and technical debt early and recommend practical solutions.

    • Continuously evaluate emerging AI technologies and determine where they can materially improve the product, development speed, customer experience or operating economics.

    • Maintain a pragmatic balance between speed, product quality, scalability, security and cost.

    • Build the technical foundation and engineering practices required to support the future growth of the technology team.

    • 10+ years of relevant experience across software engineering, technology development or technical leadership roles.

    • Exceptional, hands-on expertise in Artificial Intelligence and production-grade AI-native application development.

    • Proven experience building and deploying production-grade AI-native applications or AI capabilities, beyond basic AI API integration.

    • Strong practical understanding of LLMs, AI agents, RAG, model orchestration, prompt engineering, AI evaluation and modern AI application architectures.

    • Strong hands-on understanding of modern web, mobile, backend and cloud-based application development.

    • Experience designing scalable software architectures, APIs, databases, integrations and cloud environments.

    • Strong understanding of the trade-offs between using commercial AI APIs, open-source models and proprietary AI capabilities.

    • Ability to evaluate new AI technologies rapidly and determine their practical relevance to the product.

    • Experience with B2B SaaS products or scalable digital platforms is highly preferred.

    • Strong understanding of DevOps, CI/CD, source control, automated testing, deployment and monitoring.

    • Good understanding of application security, data protection, access control and secure software development.

    • Ability to personally review and challenge architecture, code and technical solutions and make sound technical decisions.

    • Strong problem-solving, communication and stakeholder-management capabilities.

    • Comfortable operating in a fast-moving, early-stage environment, where the Technology Lead will initially need to be highly hands-on.

    • Proven ability to lead a combination of internal engineering resources, external developers and technology vendors.

    • Previous experience as a Technology Lead, Engineering Lead, Head of Engineering, Technical Co-Founder or similar senior hands-on technology role.

    • Experience taking an AI-powered SaaS product from concept/MVP through production launch and scale.

    • Experience building AI capabilities used by real customers in production environments.

    • Experience with agentic AI, workflow automation and AI-driven business applications.

    • Experience designing technology for multilingual and multi-market products.

    • Previous experience in a startup or early-stage technology company.

    • Experience building and subsequently scaling an engineering team.

    • Strong knowledge of modern cloud platforms, application architectures and AI infrastructure.

  • We are looking for more than a traditional software engineering manager.

    The right candidate should be an AI-first technology builder who can take ownership of the technology from the beginning, challenge conventional development approaches, make strong architecture decisions, personally solve difficult technical problems and build the foundation from which a larger technology organization can eventually grow.

    The individual should be equally comfortable discussing product and business requirements with senior stakeholders, designing an AI architecture, reviewing code with developers, evaluating a new AI model, and making pragmatic decisions required to move an early-stage SaaS product rapidly toward market.

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