[Remote] Senior Software Engineer, Agentic AI (Java)

Note: The job is a remote job and is open to candidates in USA. Solovis is a leading portfolio management and analytics platform helping institutional investors navigate today's complex global markets with clarity and confidence. This is a production-focused engineering role for a senior Java developer who works agentically by default, delivering AI-augmented features and modernizations across the Java/Python/AWS stack while collaborating with existing engineers.

Responsibilities

• 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

Skills

• 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
• 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

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