Role Description A global leader in Customer Engagement Tech is seeking its next Mid-Senior .Net Developer. You will contribute to the ongoing enhancement, modernization, and support of software solutions. - Design, develop, and maintain scalable applications using C#, .NET, and ASP.NET frameworks. - Translate business and functional requirements into technical solutions and system designs. - Build, test, and integrate RESTful APIs and Backend services to support web and enterprise applications. - Write clean, efficient, and well-documented code following established development standards and best practices. - Troubleshoot, debug, and resolve application defects and performance issues in a timely manner. - Develop and execute Unit and Integration Tests to ensure code quality, reliability, and security. - Work with relational databases (e.g., SQL Server) to design schemas, write queries, and optimize data access. - Collaborate with cross-functional teams including Product, QA, and DevOps to deliver high-quality solutions. - Participate in code reviews, providing and receiving constructive feedback to improve overall code quality. - Support application deployment, configuration, and ongoing maintenance in development and production environments. - Monitor application performance and implement improvements to enhance scalability and efficiency. - Stay updated with emerging technologies and contribute to continuous improvement of development practices. Qualifications - 3+ Years of professional experience in Software Development. - Experience in parallel programming and multithreading on Windows service environments. - Solid understanding of Computer Science fundamentals - data structures, algorithms, object-oriented design and problem-solving techniques. - Experience working with SQL Server and relational database concepts. - Commitment to clean code, proper development hygiene, and avoidance of shortcuts that compromise quality. - Preferred to haves – Proficiency in XML/XSLT Programming. - Proficiency in using Git, preferably with Bitbucket workflows. - Experience using AI-assisted coding tools (e.g., Amazon Q, GitHub Copilot, Claude). - Experience modernizing legacy applications or working in mixed-technology codebases. Requirements - Ability to work independently, investigate unfamiliar systems, and drive solutions forward with minimal oversight. - Excellent problem solving and analytical skills for identifying, articulating, and resolving complex issues. - Excellent written and verbal communication skills, capable of interacting effectively with both technical and non-technical stakeholders. Benefits - Negotiable package & remuneration.

Role Description Dry Ground AI is seeking a Quality Engineer – AI, Software, & Automation Solutions to serve as the technical owner of product quality across all AI, automation, and software solutions delivered to clients. This role requires a deeply technical professional who can understand, test, and validate every component of our architecture, including: - Front-end applications - Agentic AI systems - Workflow automations - Backend services - Integrations - Voice interfaces - Data pipelines This is not a traditional QA position. The expectation is that this person will build, improve, and automate the entire quality function, using AI-enhanced development tools, creating automated test harnesses, designing diagnostic utilities, and implementing intelligent systems that help Dry Ground AI scale internally using the same technologies we deploy for clients. The ideal candidate is a builder with strong engineering instincts, a systems thinker who can test complex multi-layer AI behavior, and a professional who can collaborate across engineering and engagement teams to ensure that deliverables meet the highest standard before being presented to clients. Qualifications - 5 or more years in a highly technical QA, SDET, or full-stack engineering role. - Strong engineering fundamentals across JavaScript, TypeScript, Python, React, and API driven applications. - Experience testing AI-enabled products, conversational interfaces, or complex automation workflows. - Ability to build automated testing systems using tools such as Playwright, Cypress, or custom frameworks. - Experience with AI-enhanced development tools such as Claude Code & Github. - Strong understanding of prompt behavior, LLM variability, and common failure patterns. - Comfort working across the entire stack, including cloud services, APIs, vector databases, and real-time systems. - Excellent communication skills for coordinating across engineering and client-facing teams. Requirements - Develop QMS (Quality Management Systems) framework for internal and external solutions. - Develop comprehensive test plans across front-end, backend, automation, and AI layers. - Validate application logic, agent workflows, API integrations, prompt quality, and error handling. - Test AI agent behavior for reliability, consistency, safety guardrails, and edge case scenarios. - Build automated test suites where appropriate using modern frameworks and AI tools. - Evaluate human-in-the-loop workflows, reasoning path visibility, and agent state transitions. - Create internal automation tools that support quality checks, regression testing, and consistency validation. - Build utilities that monitor AI output correctness and detect drift or prompt failure patterns. - Implement automated validation for large-scale workflows such as n8n, custom automations, and model-driven tasks. - Design intelligent alerting systems that surface issues early in the development cycle. - Use AI coding platforms to improve velocity and maintain high quality in test development. - Build LLM-assisted testing scripts and automated evaluation harnesses for generative AI features. - Work with engineering to integrate AI into QA processes such as automated prompt scoring and conversational flow validation. - Contribute to the refinement of prompts, agent instructions, and reasoning frameworks from an accuracy and reliability perspective. - Partner with engineering to define acceptance criteria and ensure all work is testable and observable. - Coordinate closely with the engagement manager to ensure project readiness and identify risks before client delivery. - Communicate test findings clearly with actionable remediation guidance. - Serve as the final technical quality gate on all deliverables. - Establish Dry Ground AI’s QA standards and continuously improve them as we scale. - Create reusable testing templates and systems for use across all client projects. - Analyze recurring issues and lead efforts to resolve root causes. - Drive a culture of technical excellence and reliability throughout the engineering team. Benefits - Competitive compensation and performance incentives. - Remote-first work environment. - Opportunity to influence the architecture, reliability, and technical quality of AI systems across multiple industries. - A culture that prioritizes innovation, high standards, and the use of AI to scale operations.

• Provide hands-on remediation and migration of legacy SAS codebases • Repoint existing SAS workloads to a modern cloud data warehouse • Conduct code validation, reconciliation, and post-migration performance optimization • Support aggressive migration timelines while maintaining high quality and accuracy standards.

• Lead and scale Horizon3.ai’s Offensive Engineering organization • Oversee teams responsible for exploit development, offensive content, and attack automation • Set clear technical and product direction for vulnerability identification and exploitation • Partner closely with Product, Precision Defense, and Platform teams to enhance customer outcomes • Drive execution from proof-of-concept through production • Stay hands-on to guide architectural decisions and evaluate complex approaches • Build, mentor, and scale diverse teams of software engineers and offensive researchers • Collaborate across engineering, product, and GTM teams