Seeking a Full Stack engineer who can bring in AI thought leadership to the
team.
Top
Skills Required:
Hands-on
experience with AI-assisted coding tools (Claude Code, Cursor, or
similar), with the ability to guide the team on best practices and avoid
common pitfalls
Strong
Java engineering background with microservices architecture
AWS
cloud experience (Azure is a plus)
Industry
Experience:
No expectations on industry
experience, but Asset Management or Financial Services is nice to have
Key
Responsibilities
Design, develop, and maintain Java-based backend
services and APIs using Spring Boot within a DevOps delivery model on AWS
Build and maintain CI/CD pipelines,
infrastructure-as-code, and containerized deployments in AWS (ECS, Lambda,
CloudFormation, or equivalent)
Contribute to front-end development where needed,
particularly React-based interfaces for internal tools and dashboards
Implement performant, thread-safe solutions leveraging
Java concurrency and multithreading patterns
Serve as the team's AI SDLC practitioner - bring
hands-on experience with AI coding assistants (Claude, GitHub Copilot) to
establish best practices, guardrails, and effective workflows
Share lessons learned from real-world AI tool usage
- where assistants excel, where they hallucinate or produce brittle
code, and how to structure prompts, skill files, and integrations for
reliable output
Support the team's adoption of Microsoft Foundry as the
firm's AI platform, contributing to integration patterns and
experimentation
Required
Qualifications
5+ years of professional Java development with strong
command of multithreading, concurrency, and design patterns
Hands-on experience with Spring Boot for microservices
and API development
Working experience in a DevOps model on AWS - CI/CD,
containerization, infrastructure automation
Demonstrated, practical experience using AI coding
assistants (GitHub Copilot, Claude, Cursor, or similar) in real delivery
work - not just awareness, but an informed opinion on what works and what
doesn't
Understanding of AI-augmented SDLC practices including
prompt engineering for code generation, managing skill files, knowledge
files, AI-assisted code review, test generation, and documentation
automation
Familiarity with concepts such as skill files, MCP integrations,
and IDE-level AI tooling configuration
Preferred Qualifications
Front-end experience with React (component development,
state management, API integration)
Exposure to Microsoft Foundry or Azure AI services
Familiarity with asset management domain concepts
(portfolios, benchmarks, performance data, instrument types) - not
required, but useful context
Experience message queues, or event-driven
architectures
Familiarity with Python for scripting or data pipeline
support
What
We Value
A builder who has already experimented, failed, and
iterated with AI coding tools — and can fast-track the team past common
pitfalls
Strong engineering fundamentals paired with curiosity
about how AI is reshaping how we write, test, and ship code
Clear communicator who can translate technical AI
tooling decisions into practical team guidance
Ownership mentality with a bias toward shipping and
continuous improvement
Information
Locations Position Open to Only localsIndustry Information TechnologyStatus OpenJob Age 2 Day'sCreated Date 04/29/2026No.of Positions 1Duration 9 monthsZip Code
