Solutions Engineer (Java & ServiceNow)

About the role

We are seeking a Senior Solutions Engineer to join our client in a full-time capacity, based in Taguig City, Metro Manila. This is a strategic position that plays a crucial role in designing, developing, and delivering robust Java-based solutions that drive business value for our clients. As a Senior Solutions Engineer, you will be at the intersection of technology and business, translating complex requirements into scalable, high-performance solutions whilst providing technical leadership and guidance to your team. Your expertise will be instrumental in shaping our technology roadmap and ensuring we maintain our competitive edge in the software development landscape.

Key responsibilities

• Design, build, and operate production-grade software and data solutions end-to-end, from problem definition and architecture through implementation, deployment, monitoring, and continuous improvement.

• Design and implement reliable, scalable, secure, and well-governed data pipelines and data products using AWS and Snowflake across structured, semi-structured, and unstructured data sources.

• Apply strong software engineering practices, including clean code, modular design, automated testing, CI/CD, observability, secure development, and maintainable architecture.

• Partner with business and technical stakeholders to translate requirements into robust data solutions, prioritise delivery, and identify opportunities to enable advanced analytics and AI use cases.

• Use AI-assisted engineering as a standard part of daily development work to accelerate coding, refactoring, documentation, testing, debugging, and solution exploration while maintaining strong engineering judgement and quality standards.

• Build cloud-native integrations and automation on AWS, making effective use of services such as compute, storage, networking, security, orchestration, event-driven architectures, and managed AI services where appropriate.

• Own deployment, release, and production operations, including troubleshooting, root-cause analysis, performance tuning, incident resolution, peer code reviews, pair programming, and reuse of proven engineering patterns.

About you

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence / Machine Learning, or a related technical discipline.

• 8-10 years of professional experience in a hands-on software engineering, solution engineering, or data engineering role, with a proven track record of delivering production-grade systems in enterprise environments.

• Demonstrated ability to build and operate data products, cloud services, or AI-enabled solutions with measurable business outcomes and clear operational ownership.

• Deep hands-on AWS experience is required, including practical knowledge of core services for compute, storage, networking, identity and access management, security, orchestration, monitoring, and serverless or event-driven architectures.

• Strong proficiency in Java , with solid understanding of software design principles, APIs, automated testing, packaging, dependency management, and production maintainability.

• Experience with AWS AI services, including Amazon Bedrock, and familiarity with agent-based AI solution patterns, retrieval-augmented generation, model evaluation, guardrails, and responsible AI practices.

• Demonstrated habit of using AI-assisted engineering tools such as GitHub Copilot, Claude, Cursor, or similar tools as part of everyday development to improve productivity, code quality, testing, documentation, and delivery speed.

• Familiarity with harness engineering or similar AI-assisted development concepts, including structuring prompts, evaluation loops, reusable development workflows, automated checks, and feedback mechanisms to improve reliability, repeatability, and engineering quality.

• Strong hands-on engineering mindset, with a focus on code quality, sound design decisions, maintainability, and effective collaboration in team-based environments.

• Strong familiarity with the software development lifecycle, Git-based workflows, CI/CD, infrastructure-as-code concepts, automated testing, DevOps practices, and production support.