Senior Solution Engineer/Senior Java Developer

Senior Solution Engineer - Java

We are looking for a hands-on senior solution engineer who can design, build, and operate robust cloud-native data and AI solutions. The ideal candidate combines strong software engineering fundamentals with deep practical experience in AWS and Snowflake.

You will have the following qualifications:

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

7+ 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. AWS certification is preferred, ideally AWS Certified Solutions Architect

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 is preferred.

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.

Ability to translate ambiguous business problems into clear technical scopes, iterative delivery plans, and measurable success criteria.

Comfortable working with sensitive and confidential data, and partnering with governance, risk, and security stakeholders to embed controls from the start.

Strong collaboration and communication skills, with the ability to work closely with business stakeholders and cross-functional technology teams.

Preferred: background in the financial industry, with an understanding of financial markets, data sensitivity, regulatory expectations, and enterprise risk controls.**