Jobs at PALO IT

Leads sales strategy and business development for the Singapore consultancy, including market analysis, go-to-market planning, prospect engagement, pipeline development, client relationship management, proposal creation, and strategic partnerships. Collaborates with marketing, product, service, and domain teams to identify growth opportunities, tailor solutions, ensure client satisfaction, and support sustainable business expansion.

Build, test, and deploy compliance-focused workflow and document automation solutions using Power Apps, Power Automate, SharePoint, and Copilot Studio. Responsibilities include developing approval workflows, configuring SharePoint data structures, integrating submission channels and APIs, creating reporting interfaces, importing and reconciling data, supporting testing and defect resolution, applying governance controls, and producing documentation and handover materials.

Design, build, and maintain scalable backend services and RESTful APIs using Python and FastAPI. Lead backend architecture, optimize performance, ensure security, implement CI/CD and observability, mentor engineers, and apply AI-native practices including generative AI tools and prompt engineering throughout the development lifecycle.

Lead design, evolution, and governance of enterprise data architecture. Define data models, integration patterns (batch and real-time), and technology choices. Drive metadata management, lineage, data quality, privacy, and adoption of cataloging tools. Collaborate with engineering, analytics, and business teams to translate requirements into scalable cloud data solutions and promote standards, best practices, and AI-native development.

Design, implement, test, and maintain scalable Java backend systems and RESTful APIs using Spring Boot and microservices. Collaborate with architects and analysts, participate in agile ceremonies and code reviews, mentor junior developers, and improve development processes and automation.

Lead the architecture and technical delivery of scalable full-stack solutions using .NET Core and React. Design microservices, APIs, integrations, and event-driven systems while enforcing engineering standards for testing, CI/CD, security, and observability. Mentor engineers, guide architectural decisions, collaborate with product and cross-functional teams, assess technical risks, and incorporate AI-first practices into software delivery.

Manage and grow existing client accounts while developing new engagements and business opportunities. Lead client relationships, proposals, account strategy, project success, delivery alignment, budgets, and account P&L. Work with internal teams to deliver projects on time and within budget, influence senior technology decision-makers, and represent the company at industry events.

Designs and implements AI-driven workflows, system integrations, and automation solutions using n8n, Retool, Python, and Java. Assesses data-processing requirements, develops agent-based systems and RAG solutions, optimizes application performance and security, and supports scalable enterprise implementations. Collaborates with cross-functional teams during discovery, documents technical solutions, and trains junior team members on workflow automation technologies.

Leads AI-driven software engineering initiatives from discovery through delivery. Defines cloud-native architectures, service scopes, security and cost guardrails, CI/CD controls, and technical standards. Partners with clients and product teams, contributes to pitches and proofs of concept, mentors engineers, conducts code reviews, and validates AI-generated solutions. The role requires hands-on generative AI expertise and deep software architecture experience.

Own front-end architecture and user experience for production web products using React and TypeScript. Build accessible, responsive interfaces, integrate REST APIs and authentication, manage complex state, optimize performance with Next.js, and implement robust testing and security practices. Collaborate on AI-native development using generative AI tools, prompt engineering, and validation guardrails. Maintain scalable design systems, deployment workflows, and high-quality engineering standards.

Own strategic account growth and AI partnership development across enterprise and public-sector clients. Build executive relationships, create long-term account strategies, manage commercial performance, develop joint go-to-market initiatives with Microsoft and GitHub, coordinate executive engagements and events, and contribute to AI consulting offerings, thought leadership, and commercial playbooks.

Designs and maintains scalable Java backend services using Spring Boot, RESTful APIs, and microservices architectures. Responsibilities include full software development lifecycle participation, technical collaboration, automated testing, code reviews, deployment, and maintenance. The role also involves mentoring junior developers, contributing to technical decisions, supporting R&D initiatives, and ensuring clean, secure, high-performance code.

Lead manual QA efforts across the product lifecycle: design and execute functional, integration, regression, and end-to-end test cases; prepare test plans, data, and environments; report and track defects with clear evidence; analyze logs and debug issues; maintain QA documentation; collaborate with BAs and developers to clarify requirements and acceptance criteria; promote quality best practices and risk-based testing.

Design and maintain secure, scalable data pipelines and modern data lakes and warehouses for insurance use cases. Integrate structured and unstructured data, automate ingestion and transformation, implement data quality, governance, lineage, and regulatory compliance, and prepare datasets for analytics and machine learning. Collaborate with data scientists, architects, and stakeholders while documenting data solutions. Apply AI-native engineering practices, including generative AI coding tools, prompt engineering, AI-assisted development, and GenAI output validation.

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.

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.

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.