Jobs at PALO IT

Lead client-facing delivery of AI-first, full-stack products from discovery to production. Architect and build LLM-powered systems, manage scope and risks, embed with client teams, drive adoption, and mentor engineers while applying AI-native workflows, prompt engineering, and Gen-e2 methodology.

Leads the engineering organization, translating CTO strategy into execution across AI-first client and product teams. Owns architecture and AI governance, engineering standards, delivery roadmaps, token economics, incidents, technical quality, KPIs, and complex client deployments. Manages and develops engineers, runs the hiring process, builds the technical community, supports staffing and presales, and feeds delivery learnings into the company’s Gen-e2 methodology and R&D practice.

Manage and grow strategic enterprise accounts and AI partnerships (Microsoft, GitHub), build executive relationships, own account P&L and commercial performance, design joint GTM initiatives, contribute to AI offerings and executive thought leadership, and scale the partnership ecosystem across Europe.

Design and build AI-augmented prototypes and production software. Architect scalable solutions, write and review code, conduct accessibility/performance/security audits, use AI coding assistants and prompt-engineering, collaborate with clients and R&D, and stay current with AI development practices.

Owns country-specific product strategy execution, backlog management, quarterly and yearly planning, user stories, acceptance criteria, and data requirements. Partners with global and local Product, Technology, Data, Design, Marketing, and Business teams to deliver products aligned with market needs. Analyzes KPIs, user behavior, dashboards, and business data to prioritize improvements, define measurement frameworks, validate releases, and maximize product value.

Designs and maintains secure, scalable cloud data pipelines for insurance use cases including underwriting, risk management, fraud prevention, and customer experience. Integrates structured and unstructured data, builds data lakes and warehouses, automates ingestion and quality processes, and implements governance, lineage, and regulatory compliance. The role also develops datasets for machine learning and analytics while collaborating with data scientists, architects, and business stakeholders.

Designs and evolves enterprise data architectures, models, governance standards, privacy and quality frameworks, and integration solutions. The role evaluates cloud data technologies, leads data warehouse, lake, lakehouse, and mesh architecture initiatives, and supports batch and real-time pipelines. It also guides engineering, analytics, and business teams, translates business requirements into scalable solutions, and promotes data standards, metadata management, lineage, interoperability, and technical-business alignment.

Designs and develops advanced Power BI dashboards, reports, data models, DAX measures, and KPIs. Integrates data from SQL Server, Oracle, Excel, APIs, and cloud environments while applying ETL, data warehousing, performance, security, and governance best practices. Collaborates with stakeholders to create strategic data solutions and promotes a data-driven culture within enterprise environments.

Build AI-powered client products from discovery through production using full-stack engineering, AI coding tools, prompt and context engineering, and critical validation of generated outputs. Develop frontend and backend features, support testing, QA, DevOps, and CI/CD, while collaborating directly with client engineering, product, and domain teams. Translate ambiguous business needs into production-ready systems, communicate clearly with stakeholders, and contribute to consulting engagements in a hybrid Sydney-based environment.

Manage and control generation, validation, traceability, and delivery of ~182 reports across frequencies. Monitor executions and logs, detect anomalies, analyze trends, design automated controls and monitoring dashboards, document rules and sources, support users, and propose automation and quality improvements to ensure accurate, auditable reporting.

Design, develop, and maintain Java backend microservices and RESTful APIs. Integrate relational and NoSQL databases, implement data access via Hibernate/JPA, write unit and API tests, improve CI/CD pipelines, apply security best practices, perform profiling and production troubleshooting, and collaborate in Agile teams.

Develop, maintain, and evolve enterprise Microsoft-based applications. Analyze requirements, design scalable solutions, implement features, write and optimize SQL Server queries, integrate APIs and Azure services, participate in code reviews, resolve incidents, and collaborate across multidisciplinary teams.

Lead cross-functional teams to design and implement AI-driven applications on GCP using React 18, TypeScript, and Python FastAPI; integrate AI via Google ADK; manage data in Firestore and Cloud SQL; use generative AI tools and prompt-engineering best practices; conduct architecture and code reviews; coordinate work with GitHub Projects and document via Claude Code.

Lead engineering quality and AI-native Gen-e2 adoption across PALO IT Thailand. Hands-on technical leadership on select projects, set engineering standards and playbooks, audit AI-assisted development, mentor Tech Leads, support presales with technical credibility, and enforce quality gates, CI/CD, testing, and security practices.

Lead end-to-end delivery of AI-first, full-stack products for enterprise clients: lead discovery, architect and build AI-powered systems, scope and manage delivery to production, embed with client teams, and champion AI-native practices and prompt/context engineering.

Design, build, and integrate automated testing frameworks for frontend and backend systems; embed tests into CI/CD pipelines; monitor performance, troubleshoot issues, and collaborate with cross-functional teams using GitHub and Agile practices to ensure high-quality AI-enabled applications.

Lead design and development of cross-platform mobile apps using Flutter/Dart. Implement responsive UI, state management, native integrations, API/GraphQL connections, CI/CD, observability, storage, testing, app store publishing, and provide level 2 support while collaborating on architecture and working in Agile.

Lead and own technical direction for engineering teams, embedding AI/GenAI into development workflows. Provide full-stack architecture and code guidance, enforce GenAI best practices, mentor engineers, ensure delivery quality via CI/CD and testing, collaborate with clients and sales, and scale reusable assets using the Gen-E2 methodology.

Lead design and delivery of complex, scalable software using AI-assisted development. Mentor engineers, implement CI/CD and DevOps practices, establish AI/GenAI best practices and guardrails, validate AI-generated outputs, and contribute to reusable accelerators, presales, and Gen-E2 methodology.

Lead AI-native fullstack development using AI-augmented practices. Ensure code quality, implement CI/CD and DevOps automation, design scalable secure solutions, integrate AI enhancements, validate GenAI outputs, mentor teams, and stay current with AI technologies.