Jobs at Kadel Labs

Designs and develops scalable storage and networking solutions for Kubernetes infrastructure. Responsibilities include building distributed systems, debugging Kubernetes clusters and performance issues, developing cloud and multi-cluster capabilities, automating processes, identifying security risks, and collaborating in Agile/Scrum release cycles. Requires extensive C/C++ software development, Kubernetes expertise, CKAD certification, Linux systems knowledge, networking, virtualization, and distributed storage experience.

Owns risk data pipelines, portfolio MIS, and recurring reporting for a US credit card portfolio. Builds dashboards covering delinquency, roll rates, vintage curves, and KPIs; develops SQL and Python pipelines; performs data quality checks and reconciliation; resolves source-data issues; and uses AI tools to automate reporting and self-service analytics.

Lead the architecture and development of a Kubernetes-native HCI platform, focusing on storage subsystems, CSI drivers, CNI networking, embedded Linux, kernel components, and high-performance networking. Drive benchmarking, reliability, scalability, failure handling, and root-cause analysis for complex customer issues. Provide hands-on technical leadership through code reviews, design guidance, mentorship, and collaboration with Product, QA, Support, and Services teams.

Owns HCI build and release management, hardware certification, infrastructure engineering, and platform validation. Responsibilities include maintaining CI/CD pipelines, security scanning, validating server, storage, and network hardware, conducting performance and resiliency testing, optimizing compute, storage, and networking paths, integrating custom hardware with Kubernetes, and automating deployments with infrastructure-as-code tools. The role also supports customer PoCs, escalations, vendor coordination, documentation, architecture discussions, and code quality improvements.

Own the multi-quarter product roadmap, product requirements, release execution, and product strategy for cloud-native infrastructure products. Lead cross-functional collaboration across Engineering, QA, Sales, Marketing, Support, and Field teams. Manage a small team supporting product marketing and technical publications while driving customer research, competitive analysis, go-to-market initiatives, technical demonstrations, and product collateral across Kubernetes, multi-cloud, storage, AI/ML, and LLM technologies.

Perform credit risk analytics across the US credit card lifecycle, including acquisitions, account management, and collections. Analyze portfolio performance, support scorecard development and validation, conduct segmentation and champion-challenger analyses, and assess policy impacts. Apply machine learning and AI techniques to improve risk models and insights. The role requires US card portfolio experience, strong Python and SQL skills, advanced Excel proficiency, knowledge of credit bureau data and underwriting, and strong communication skills.

Manage key client accounts for an IT services company, serving as the primary contact for business and technical needs. Build relationships, drive retention and satisfaction, identify farming, upselling, and cross-selling opportunities, support proposals and negotiations, coordinate with technical and delivery teams, resolve escalations, monitor account health, and develop growth strategies. Travel to client locations as needed.

Design, implement, and optimize scalable MongoDB data solutions for enterprise applications. Responsibilities include schema design, CRUD operations, indexing, query optimization, aggregation pipelines, .NET/C# integrations, replication, sharding, backup and recovery, monitoring, security, data lifecycle management, change streams, and search capabilities. The role also collaborates with backend teams on APIs and microservices.

Lead cross-functional engineering teams across front-end, back-end, QA, and integration. Drive technology strategy, architecture, scalable application development, SDLC execution, cloud adoption, AI initiatives, code quality, compliance, and innovation. Manage stakeholder communication, recruitment, mentoring, performance development, and technical roadmaps while overseeing secure, reliable, and high-quality solutions using Azure, .NET Core, React, Docker, and Kubernetes.

Designs and automates cloud infrastructure, CI/CD pipelines, and containerized deployments. Manages Kubernetes and Azure environments, infrastructure as code, monitoring, scalability, service reliability, incident response, and postmortems. Supports system design, capacity planning, production engineering, and continuous service improvement. The role also integrates security scanning and other tooling into established delivery pipelines while collaborating across technical teams.

Own software features end-to-end by writing precise specifications, defining acceptance criteria, and validating AI-assisted outputs. Build APIs, data layers, services, integrations, and engineering foundations for AI-native workflows. Design generator-critic pipelines, evaluate AI tools, diagnose AI output failures, and develop production solutions using LLM APIs, RAG, vector databases, and agent frameworks. Collaborate in Agile or Kanban environments while maintaining autonomous ownership of requirements, development, quality, and delivery.

Leads a data engineering team responsible for designing scalable batch and near-real-time ETL/ELT pipelines, data models, and Microsoft Fabric solutions. Builds SQL Server and MongoDB platforms, Power BI semantic models, and AI-enabled development workflows. Mentors engineers, drives data quality, security, governance, performance, and cost optimization, and collaborates with technical and business stakeholders to deliver analytical and operational data solutions.