Senior Agentic Software Engineer (Java)

Job summary

SENIOR AGENTIC SOFTWARE ENGINEER (JAVA) Sol*** is a leading portfolio management and analytics platform helping institutional investors navigate today's complex global markets with clarity and confidence. Backed by Insight Partners, we're building the next chapter of growth by investing in people and product to raise the bar on quality and client outcomes.

Qualifications

• 5–9 years of professional software engineering experience.
• Strong fluency in Java, with solid working knowledge of Python on AWS.
• This is a Java-specialized seat.
• 6+ months of serious agentic tool use (Claude Code, Cursor, or equivalent) on production work, not pilots or side projects.
• Production ownership history: you have shipped non-trivial systems and been on the hook when they broke.
• At least one out-of-depth experience: a stack switch, domain change, or greenfield build in unfamiliar territory.
• You know what it feels like to be uncomfortable and productive at the same time.
• The ability to catch non-obvious agent errors and concrete heuristics for when to trust output and when to verify.
• STRONG PLUS
• Experience with financial services, institutional investment platforms, or other high-correctness, regulated software domains.
• Familiarity with brownfield modernization: improving existing systems with agents rather than rewriting them.
• Background integrating or reviewing work you did not personally author.

Responsibilities

• At Sol***, you'll join a tech-forward, growth-minded team that believes in learning fast, thinking big, and delivering meaningful impact for asset owners worldwide.
• You will deliver AI-augmented features, modernizations, and new capabilities across our Java/Python/AWS stack.
• You will also pair with existing engineers to transfer agentic working habits — not by lecturing, but by working together on real problems.
• Deliver production features and modernization work across our Java/Python/AWS stack using AI-augmented development as your primary mode of authorship.
• Pair with existing engineers to build agentic practice organically through working sessions on real deliverables, not classroom instruction.
• Participate in AI-augmented PR reviews while contributing to pattern libraries and review checklists.
• Own production systems end-to-end: ship real things, stay accountable when they break, and close the loop.
• Bring concrete judgment about when to let an agent run and when to intervene — and share that judgment with the team.

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