Associate Director Staff Engineer - Software

• This role has transitioned into a technical leadership track.
• This role has developed the skills to partner and influence other teams toward business targets and goals.
• This individual is building deep, specialized expertise and is able to engage within technical and business teams.
• This role might serve as a SME on a team or lead a small team of technical experts supporting a larger effort, and may consult to business teams.
• When successful, this individual may be recognized for leading a particular technical implementation or leveraging sophisticated knowledge to benefit a larger team.
• Takes full responsibility of complex, cross-functional projects and ensures successful execution and delivery.
• Demonstrates a proactive approach to resolving challenges and holds themselves accountable for the successes and challenges of broader team efforts.
• Communicates within team and with team's business stakeholders to influence architectural decisions and trade- offs in the lane.
• Effectively communicates complex technical concepts to both technical and non-technical stakeholders and clearly explains moderately complex team-level concepts.
• Recognizes viable opportunities for innovation and actively drives the adoption of innovative techniques and tools within the team.
• Leads innovation efforts in line with organizational goals.
• Participates in developing creative solutions to complex problems.
• Demonstrates an exceptional ability to break down intricate
  problems into manageable components, conducting thorough analysis to identify root causes and interdependencies.
• Encourages collaborative thinking and cohesiveness within the team; acts as a bridge between teams, ensuring synchronization of efforts.
• Generally, builds rapport and collaborates effectively with a broad spectrum of people and offers help to other team based on a specific area of expertise.
• Guides and mentors team members by providing feedback and coaching, especially during challenging situations. Encourages people to challenge themselves and helps others stretch their capabilities

General Skills:

• 6 – 8 Years of software engineering experience
• Experience managing/maintaining distributed systems.
• Conversant in many technologies and languages, able to learn new technologies quickly
• Proactively applies industry leading technology trends, best practices, design principles and patterns, and methods including Agile software development, iterative delivery, and cloud computing.
• Experience and proficiency with cloud platforms and patterns, preferably AWS.
• Uses critical thinking to reach conclusions and analytical thinking for problem solving in support of achieving desired outcomes.
• Applies enthusiasm for continuous learning to improve results and shares with others.
• BS degree in a computer related field
• Excellent communications

Technology Required:

• Core Tech: Java, J2EE, Spring Boot, REST APIs, Maven
• Rule Engines: IBM ODM, Drools, Kogito, BPMN, JBPM
• Cloud Platforms: AWS , Azure (preferred), Kubernetes, Docker, Openshift
• Data & Format Handling: XML, JSON
• Monitoring & Testing: OpenTelemetry, Prometheus, Grafana, Jenkins, GitHub Actions
• Automation Tools: Customized rule development & testing platforms, synthetic data generators, regression suites
• Agile Tools: Jira, Confluence, Miro    

Day to Day Responsibilities:

• Own delivery of decisioning platforms end-to-end, ensuring on-time, high-quality implementation of core components of Decisioning infrastructure that power credit, pricing, and risk strategies.
• Build and deliver reusable decisioning components for rule authoring, versioning, simulation, testing, and observability, ensuring solutions are scalable, reusable, and explainable.
• Lead the rollout of a cloud-native, modular decisioning platform using Drools, Java, and Spring Boot, modernizing legacy mainframe-driven logic into centralized, API-driven services.
• Establish and manage delivery frameworks, governance processes, and best practices for business rule lifecycle, from harvesting through production deployment.
• Build and enforce robust automation and testing frameworks to guarantee reliability and regression safety across decisioning services.
• Drive operational excellence by integrating telemetry, monitoring, and automated feedback loops into the platform, ensuring proactive detection of issues and continuous optimization of rule effectiveness.
• Mentor engineering teams and provide hands-on leadership to ensure execution quality, unblock delivery challenges, and maintain alignment to architectural vision.
• Present progress, risk