Jobs at Kadel Labs

Analyze and reverse-engineer a complex legacy SQL Server platform, including application code, stored procedures, functions, and lookup tables. Build accurate production-safe data extracts, identify data-quality issues, support schema mapping and migration reconciliation, compare data against application screens, and document business rules. The role requires extensive T-SQL expertise, familiarity with C#/.NET data access, daily use of LLM coding tools, and rigorous validation of results.

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.