Description
Our Employee Value Proposition
At Amtech, our people are our greatest differentiator. We create an environment where you can:
Purpose
Shape the future of manufacturing and supply chain operations by delivering mission-critical enterprise software used by industry-leading organizations.
Growth
Access continuous learning, leadership development, and cross-portfolio opportunities through Vista’s global network — accelerating both technical and managerial career paths.
Culture
Work in a collaborative, transparent, and people-first environment where values, accountability, and integrity guide every decision.
Innovation
Engage with cutting-edge technologies, including AI-driven automation, and contribute to modernizing financial systems and operational processes across the business.
Position Overview
We are seeking a Senior Software Engineer to lead technical improvements across multiple modules and teams on the EnCore ERP platform. You will own complex projects and major features while establishing standards, guiding architecture decisions, and improving how the entire team delivers safely and efficiently. At this level, you are a trusted technical leader who balances urgent customer needs with long-term modernization—and who sets the bar for code quality, testing, and production safety across the organization.
This role emphasizes team-level impact, technical leadership, production-risk judgment, and incremental modernization of large legacy systems. You will mentor developers, lead incident response, establish database governance and testing standards, and guide architectural choices. You will think about deployment risk, customer variation, and business priorities—not just code correctness.
Key Responsibilities
- Own projects or major features at the team level, including architecture, delivery strategy, team coordination, and measurable business outcomes.
- Lead technical standards for database changes, code review, testing, logging, and incident response across multiple modules.
- Guide architectural decisions that balance immediate delivery against long-term maintainability, deployment risk, and team capability.
- Lead production incidents involving financial, inventory, or shipping data—determining root cause, safe recovery, and preventive actions.
- Design incremental modernization strategies for complex legacy systems, prioritizing high-impact, bounded improvements over full rewrites.
- Establish database governance including change standards, schema compatibility, multi-customer testing, and safe migration procedures.
- Mentor and train developers in both technical skills (PPJ, WiseJ, SQL Server, transaction design) and professional judgment (prioritization, risk assessment, incident response).
- Conduct thorough code reviews of changes to critical systems, focusing on business correctness, transaction safety, concurrency, and testability.
- Diagnose systemic issues(frequent defects, slow deployments, onboarding challenges) and propose solutions that improve team effectiveness.
- Communicate across boundaries with product, QA, customer success, and business leadership to understand priorities and constraints.
AI Proficiency (L3: AI Power User)
Scope: Team-wide productivity; architect AI workflows; mentor others; set organizational patterns
- Workflow integration: Embed AI across your team's development lifecycle—code generation, testing, documentation, refactoring, and knowledge transfer.
- Output risk ownership: Design validation steps appropriate to task criticality; ensure AI-generated work meets team standards before shipping.
- Team mentoring: Teach developers at all levels how to use AI effectively; know when to use AI and when to rely on human judgment.
- Pattern design: Establish team-wide standards for AI usage (e.g., "AI for boilerplate and documentation, always review; AI for core logic only with peer review").
- Tool selection and governance: Evaluate AI tools (Claude, Copilot, etc.); recommend adoption based on team needs and security constraints.
- Continuous improvement: Identify where AI can improve developer productivity without sacrificing quality or security.
Examples:
- Design a team-wide AI workflow for onboarding new developers on complex legacy modules.
- Establish code review standards that include AI-generated code validation requirements.
- Use Claude to generate comprehensive documentation, test plans, and architectural diagrams—with team validation.
- Mentor peers and team members on effective AI usage; help them identify when AI is appropriate vs. when human judgment is essential.
- Propose AI-assisted approaches to common pain points (slow tests, documentation gaps, refactoring burden).
- Set policies and guidelines for your team on data safety, secrets, and appropriate AI tool usage.
Required Qualifications
Technical Leadership
- Expert C# architecture and patterns:
- Deep understanding of dependency injection, service composition, and testable boundaries around legacy code.
- Ability to design for incremental improvement: extracting bounded capabilities, running old and new in parallel, and rolling back safely.
- Expertise in transaction design, including outbox patterns and separation of database transactions from external calls.
- Proficiency with async/await, error handling, and graceful degradation in distributed systems.
- Expert SQL Server and database governance:
- Deep understanding of locking, concurrency, isolation levels, and deadlock prevention.
- Ability to design safe, rerunnable migration scripts for large production tables with considerations for blocking, compatibility, and rollback.
- Expertise in data validation, reconciliation queries, and detecting partial failures.
- Standards for database change management: idempotency, parameterized queries, peer review, and phased deployment.
- Understanding of customer schema variations and how to test against representative database snapshots.
- Testing and quality standards:
- Ability to introduce automated testing around static globals, databases, and legacy code without large rewrites.
- Design of representative test fixtures and characterization tests that preserve existing behavior.
- Understanding of what to test: success, validation failure, database failure, rollback, and concurrency.
- Recognition that tests must be maintainable; an unmaintained test is a liability.
- Production systems and incident response:
- Leadership of financial or inventory incidents: containment, root-cause analysis, safe recovery procedures, and preventive actions.
- Understanding of financial reconciliation and the principle that records must never be manually changed without audit trails.
- Systematic diagnosis using logs, execution plans, database analysis, and production telemetry.
- Design of observability: correlation IDs, structured logging, and business-context metrics.
- Modernization and architecture:
- Experience assessing which components should be modernized first based on business value, defect rate, and change frequency—not code appearance.
- Ability to compare old and new approaches (e.g., optimistic vs. pessimistic concurrency, .NET Framework vs. modern .NET) with explicit trade-offs.
- Skill at running old and new implementations in parallel, gradually shifting traffic, and rolling back if needed.
- Recognition that full rewrites carry hidden risk; incremental improvement is often safer and more effective.
Leadership & Influence
- Technical decision-making: Lead discussions o
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