Senior Software Engineer

• Lead moderately complex initiatives and deliverables within technical domain environments
• Contribute to large scale planning of strategies
• Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments
• Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures
• Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements
• Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals
• Lead projects and act as an escalation point, provide guidance and direction to less experienced staff

Required Qualifications:

• 4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:

• Lead complex initiatives and deliverables within technical domain environments
• Contribute to large scale planning of strategies
• Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments
• Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures
• Design and build enterprise-grade full stack solutions using Java and modern frameworks.
• Develop backend services and APIs using Spring / Spring Boot, following API-first design principles.
• Contribute to architecture and design decisions across services, data flows, integrations, and platform capabilities.
• Ensure solutions are scalable, maintainable, secure, and production ready.
• Design and integrate GenAI-powered workflows into engineering platforms and SDLC processes, from experimentation through production deployment.
• Build and operate services leveraging LLMs for reasoning, generation, validation, and analysis, using structured outputs, safety guardrails, and deterministic behaviors.
• Implement tool-calling and agent-based orchestration patterns (e.g., MCP-style architectures) to enable AI interaction with services, APIs, and enterprise systems.
• Hands-on experience integrating LLMs into real, production-grade applications or platforms, not just prototypes or POCs.
• Strong understanding of prompt engineering, schema-based outputs (JSON/function calling), context management, and fallback / retry strategies.
• Experience with agentic or tool-calling frameworks (MCP or equivalent concepts), including tool contracts, orchestration logic, and failure handling.
• Ability to evaluate, benchmark, and tune LLM behavior for accuracy, consistency, cost, and latency.
• Demonstrated judgment in deciding when GenAI adds value versus traditional deterministic engineering approaches.
• Experience applying GenAI to automation and quality use cases such as test generation, validation, diagnostics, documentation, and change-impact analysis.
• Experience with automation frameworks at UI, API, or integration layers.
• Ability to design automation as reusable platform services, not isolated scripts.
  • Exposure to BDD-style design or requirements-driven validation is preferred.