<p>We are seeking an Integration Engineer to provide technical leadership across the end-to-end development and delivery of new insurance products and capabilities, enabling new business opportunities and operational efficiencies. This role will lead the design, development, and integration of underwriting frameworks and platforms across multiple lines of business using Agile and DevOps methodologies.</p><p>This position requires hands-on development experience, deep integration expertise, and the ability to technically lead globally distributed teams to deliver scalable, secure, and high-quality cloud-native platforms and services aligned with business priorities.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><p>· Provide hands-on technical leadership for application design, development, and integration of secure and scalable solutions.</p><p>· Lead end-to-end development, implementation, and integration of new insurance products and packages using underwriting frameworks.</p><p>· Design and implement platforms enabling continuous delivery of features and capabilities aligned with business priorities.</p><p>· Partner closely with Product Managers/Owners, Business Analysts, Developers, and enterprise teams to define optimal technical solutions.</p><p>· Lead high-level design efforts, perform code reviews, and guide implementation by development teams.</p><p>· Develop select modules while reviewing and mentoring other engineers’ code.</p><p>· Mentor and coach junior engineers across multiple Scrum teams.</p><p>· Leverage an Agile-based operating model across distributed teams.</p><p>· Prepare technical documentation and deliver sprint and system demonstrations.</p><p>· Manage production workloads and act as an SME for Level 3 production support issues.</p><p>· Perform complex troubleshooting, root cause analysis, and resolution of critical production defects.</p><p>· Communicate status, risks, and dependencies in accordance with agreed communication plans.</p>
<p>Job Summary</p><p>We are seeking a <strong>Machine Learning Engineer</strong> to design, build, validate, and deploy machine learning solutions that support products and applications in a production environment. This role focuses on the full ML lifecycle—from data pipelines and model training to validation, deployment, monitoring, and documentation—working closely with cross‑functional teams to deliver scalable, reliable solutions.</p><p><br></p><p>Key Responsibilities</p><ul><li>Design, implement, refine, and validate machine learning algorithms for products and applications</li><li>Design and develop robust data pipelines, including data ingestion, validation, cleaning, and monitoring</li><li>Train machine learning models; validate model accuracy and performance prior to deployment</li><li>Deploy validated machine learning models into production environments and support ongoing monitoring</li><li>Design proof‑of‑concept (POC) solutions and contribute to studies supporting future product or application development</li><li>Test and evaluate machine learning solutions; complete case studies, testing, and reporting</li><li>Research, write, and maintain technical documentation, including:</li><li>Evaluation plans</li><li>Confluence pages</li><li>White papers and presentations</li><li>Test results, technical manuals, and formal recommendations</li><li>Collaborate with teams outside the immediate work group and represent the team when addressing technical issues related to assigned projects</li></ul><p><br></p>