WCF Services Specialist

Salary Range: 180000 to 200000 (Currency: USD) (Pay period: per-year-salary)

The Role

As a WCF Services Specialist, you will act as a technical expert and investigator for an established enterprise platform built on Microsoft WCF technologies.

This role goes beyond traditional application support. We are looking for someone who is naturally curious and enjoys dissecting complex systems to understand how they work, why they behave the way they do, and where opportunities exist for improvement.

You will analyze service interactions, investigate recurring operational issues, document platform behavior, identify root causes, and recommend low-risk technical improvements that enhance reliability, maintainability, and performance.

The ideal candidate will be comfortable working within a mature legacy environment, able to pull on technical threads that appear unusual or inconsistent, and capable of transforming tribal knowledge into documented engineering understanding.

This is a highly hands-on role focused on technical diagnosis, root-cause analysis, operational excellence, and continuous improvement.

What You'll Be Doing

WCF Platform Analysis & Troubleshooting

• Support, maintain, and improve enterprise applications built using Microsoft WCF.
• Analyze existing WCF services, configurations, endpoints, bindings, and communication patterns.
• Investigate timeout issues, communication failures, startup delays, and performance bottlenecks.
• Diagnose complex production issues and identify underlying root causes rather than simply addressing symptoms.
• Analyze service functions, client calls, API signatures, and service contracts.
• Work with full-duplex WCF channels and callback mechanisms.
• Support and improve WPF-to-WCF communication workflows.
• Conduct root-cause investigations across distributed applications.

Technical Investigation & Documentation

• Analyze service behavior and system interactions to identify unusual patterns, weaknesses, and undocumented functionality.
• Pull on technical threads that appear inconsistent, unreliable, or difficult to explain.
• Investigate recurring operational practices and determine the technical reasons behind them.
• Examine why certain workarounds exist and validate whether they remain necessary.
• Document platform architecture, service relationships, technical findings, operational behaviors, and known issues.
• Transform historical knowledge and undocumented processes into maintainable engineering documentation.

Performance & Maintainability Improvements

• Identify low-risk opportunities to improve performance, reliability, maintainability, and operational stability.
• Evaluate why routine service restarts may be occurring and determine whether the issue stems from design flaws, configuration problems, coding defects, resource utilization, or operational practices.
• Recommend targeted improvements that reduce operational burden without introducing unnecessary risk.
• Reduce technical debt through incremental and well-tested changes.
• Contribute to long-term modernization initiatives where appropriate.

AI-First Engineering Practices

• Utilize AI-assisted tools and modern engineering workflows to accelerate investigation, documentation, testing, and knowledge discovery.
• Leverage AI technologies to better understand legacy codebases and service interactions.
• Promote thorough documentation, validation, and testing practices across the platform.
• Help establish an AI-first mindset for engineering analysis, continuous learning, and operational excellence.

What Success Looks Like

In your first 6 to 12 months, success means:

Critical production issues are consistently resolved through root-cause analysis rather than temporary workarounds.

The reasons behind recurring operational practices, including service restarts, are understood, documented, and addressed where appropriate.

WCF services demonstrate improved stability, performance, reliability, and maintainability.

Platform architecture, service interactions, and operational knowledge are documented and accessible.

Technical debt and long-standing issues are identified with clear improvement plans.

Low-risk enhancements are implemented with measurable operational and performance benefits.

Engineering and support teams have greater confidence in diagnosing and resolving platform issues.

 AI-assisted analysis, testing, and documentation practices help reduce knowledge gaps and improve team efficiency.

What You Should Have

• 8+ years of experience developing, supporting, and troubleshooting enterprise Microsoft .NET applications.
• Deep hands-on experience with Windows Communication Foundation (WCF).
• Strong knowledge of:
• Service Contracts
• Data Contracts
• Operation Contracts
• Endpoints
• Bindings
• Client Proxies
• Service Configuration
• API Signatures
• Experience troubleshooting and optimizing complex WCF environments.
• Expertise diagnosing:
• Timeout exceptions
• Service startup issues
• Communication failures
• Memory and resource utilization problems
• Performance bottlenecks
• Production stability concerns
• Experience working with full-duplex WCF communication and callback contracts.
• Experience supporting WPF applications that consume WCF services.
• Strong root-cause analysis and investigative troubleshooting skills.
• Experience working with large, long-lived enterprise applications and legacy technology platforms.
• Demonstrated ability to reverse-engineer existing systems and understand undocumented behaviors.
• Strong technical documentation skills.
• Experience identifying low-risk optimization and modernization opportunities.
• Excellent problem-solving, analytical, and communication skills.
• Ability to collaborate effectively with developers, architects, support teams, and business stakeholders.

Nice to Have

• Experience modernizing or migrating legacy WCF applications.
• Experience with both .NET Framework and modern .NET platforms.
• Experience with REST APIs and service modernization initiatives.
• Experience in financial services, capital markets, asset management, or other highly regulated environments.
• Familiarity with application monitoring and diagnostics tools.
• Experience working in Agile delivery teams.
• Experience leveraging AI-assisted engineering tools such as GitHub Copilot, Claude Code, Cursor, ChatGPT, or similar technologies.
• Experience using AI to accelerate code analysis, technical documentation, testing, and root-cause investigation.