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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # API Technical Lead - Payments Platform Modernization - **Company:** Tekshapers Inc - **Location:** Alpharetta, GA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** ASP.NET, .NET Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Performance Management, Automation of Tests, Microsoft Azure, C Sharp (Programming Language), Cloud Computing, Code Generation, Continuous Integration, Data Validation, Data Masking, Software Debugging, Software Design Patterns, DevOps, Key Management, Routing, OAuth, Open Web Application Security, PCI Data Security Standards, Openid Connect, Swagger, Message Oriented Middleware, Reverse Engineering, Software Deployment, Management of Software Versions, Openapi, Azure Service Bus, Datadog, Enterprise Application Integration, Data Logging, Data Processing, .NET Core, Postman, GitHub Copilot, Software Security, ReadyAPI, Caching, Generative AI, Backend, Rate Limiting, Event Driven Architecture, Build Management, Containerization, Kubernetes, Deployment Automation, Production Code, Apache Kafka, OPUS (Software), Api Design, Api Gateway, Restful APIs, Pagination, Domain Driven Design, Splunk, Software Version Control, Dynatrace, Api Management, Docker, Key Vault, Microservices - **Published:** August 5, 2026 - **Apply:** https://www.dice.com/job-detail/e5a48a25-90ad-44b7-b1c0-33a1d13aa978 ## About the Role Primary stack: .NET Core / ASP.NET Core / C# Cloud: Azure Experience: 12-15 years hands-on, with a minimum of 8 years as an API Lead, 12-15 years of hands-on engineering experience, including a minimum of 8 years as an API Lead. Strong hands-on expertise in .NET Core, ASP.NET Core and C#. Delivery experience across both monolithic and microservices-based .NET applications. Proficiency with Git version control. Experience working in global delivery or offshore engagement models. Technical Leadership Proven experience leading API engineering teams while remaining hands-on with code. Ability to write, review and debug production code - demonstrable in a live technical assessment. Strong command of design patterns, API standards, development guidelines and engineering best practices, sufficient to author or critique architecture decision records. Strong ability to interpret ADR, HLD and LLD documentation and translate it into features and stories. Confidence to challenge architectural decisions and escalate design gaps constructively. API Development & Modernization Recent, current delivery experience on API development and modernization or re-platforming programs. Deep RESTful API design: resource modelling, versioning, idempotency, pagination, error contracts, backward compatibility. Contract-first development with OpenAPI/Swagger. End-to-end understanding of API infrastructure - API gateways, facade and BFF layers, proxy chains, routing, rate limiting, throttling and caching. Integration patterns: synchronous and asynchronous messaging, event-driven architecture, retries, circuit breakers, timeout budgeting. Microservices architecture and decomposition of monolithic platforms. Payments Domain Hands-on delivery experience on a payments platform. Working knowledge of payment processing engine, payment management and account management domains. Understanding of the payment lifecycle - authorization, capture, clearing, settlement, posting, reconciliation, reversals and exception handling. Familiarity with payment messaging standards and rails relevant to the platform. Awareness of the regulatory and compliance environment around payments, including PCI-DSS and audit traceability obligations. Cloud, DevOps & Automation Azure - hands-on experience with API Management, AKS/App Services, Functions, Key Vault, messaging services and managed identity. CI/CD - end-to-end pipeline design and ownership, including automated testing, security scanning and progressive deployment strategies. Docker - containerization, image hygiene, multi-stage builds. Kubernetes - deployments, scaling, configuration and secrets management, resource governance, and live troubleshooting of running workloads. Automation - infrastructure as code, environment provisioning, deployment and test automation. Azure is the primary platform. Equivalent hands-on experience on AWS is acceptable where Azure exposure can be demonstrated., Sensitive data handling - masking, tokenization and minimization of PII and cardholder data. Familiarity with the OWASP API Security Top 10. AI Engineering & Tooling Working, hands-on experience with GitHub Copilot and Claude Opus for AI-assisted development. Proven delivery of AI projects involving forward engineering (code generation, modernization) and reverse engineering (code understanding, documentation, refactoring) using AI tooling. Working understanding of agentic AI architecture - sufficient to execute and operate a pipeline. Ability to run and troubleshoot the client's existing AI framework. Ability to critically review and validate AI-generated code, specifications and documentation. Exposure to Retrieval-Augmented Generation (RAG) architectures. Deep AI expertise, model development, training or fine-tuning is not required. The role applies AI tooling to the engineering estate and validates its output; it does not build AI capability. Good to Have These add value but are not filters. Exposure to one or more items within a bullet is sufficient; specific tooling is not a screening criterion. Architecture governance - prior experience authoring ADRs or owning an architecture governance function. Observability tooling - hands-on with one or more of OpenTelemetry, Application Insights, Splunk, Dynatrace or equivalent. Contract and API test automation - exposure to one or more of Pact, Postman/Newman, RestAssured or Karate, particularly consumer-driven contract testing. Event-driven messaging at scale - Kafka, Azure Service Bus, Event Hubs or equivalent. Performance engineering for high-volume transaction systems - load modelling, latency budgeting or throughput tuning across multi-hop API paths., Hands-on credibility. Technical depth must be demonstrable, not narrated. This role does not suit a purely advisory or coordination profile. Constructive challenge. Comfortable reviewing client-authored designs and raising what is missing, respectfully and clearly. End-to-end ownership. Accountability extends beyond own deliverables to whether downstream teams can do their work. Client-facing communication. Able to hold technical discussions with client architects and operations leadership and articulate design trade-offs clearly. Cross-functional collaboration. Works effectively across UI, platform, gateway, operations and downstream consumer teams. Documentation discipline. Records design decisions and contracts so the wider group stays aligned. Sound judgement. Willing and able to act as the human quality gate on AI-assisted output. Stakeholder engagement. Strong communication and client engagement skills across business and technology audiences. Business translation. Able to translate business challenges into practical technical solutions. Outcome orientation. Focused on delivering against customer requirements. ## Description We are hiring an API Technical Lead to own API architecture, design and implementation for a large-scale payments platform modernization program. This is a hands-on role. The successful candidate will lead the API workstream while continuing to write, review and debug code. They will work within the client's established Architecture Decision Record framework, govern design quality across the API estate, and take accountability for the end-to-end integrity of the API layer - including the observability and security contracts that downstream systems depend on. The role demands breadth of understanding across the full stack - from front end through gateway and proxy layers to backend services and cloud infrastructure - combined with the depth to identify a design defect and challenge it. The platform is built on .NET Core and ASP.NET Core across both monolithic and microservices architectures. AI-assisted engineering is central to the modernization approach: the successful candidate will use GitHub Copilot and Claude Opus for forward engineering - code generation and modernization - and reverse engineering - code understanding, documentation and refactoring - and will take accountability for validating what those tools produce. Key Responsibilities API Architecture & Design Lead API architecture, design and implementation for the payments modernization program. Own the end-to-end API call path - from UI through the interface layer, API gateway and proxy tiers to backend services and downstream systems. Define and enforce API contracts, versioning strategy, error handling standards and integration patterns. Design for idempotency, resilience and failure recovery across a high-volume transaction platform. Architecture Governance Work within and uphold the client's two-tier ADR framework: foundational ADRs covering design patterns, API standards, development guidelines, best practices and architecture alignment; and domain-driven ADRs covering the payment processing engine, payment management and account management. Review architecture and design artifacts critically, and raise gaps, inconsistencies or omissions rather than implementing to a flawed specification. Maintain alignment between platform-level standards and domain-level design decisions. .NET Development & Integration Hands-on development across .NET Core, C# and ASP.NET Core, spanning both monolithic and microservices-based applications. Design, build and deploy AI-enabled architectures integrated with .NET Core and ASP.NET Core applications. Ensure smooth integration of AI components with .NET-based enterprise systems. Provide technical guidance on REST APIs, microservices and enterprise integration patterns. Delivery Accountability Guarantee the retrieval and posting contracts across the platform - ensuring downstream teams and consuming systems can access the data they need, in the right shape, with defined freshness guarantees. Conduct code and design reviews; set and hold the technical bar for the team. Mentor and guide .NET development teams and AI engineers, and provide technical direction across the API workstream. Interpret ADR, HLD and LLD documentation and convert it into features and stories for the delivery team. Support project delivery from architecture definition through to production deployment. Engineering Practice Drive CI/CD, containerization and automation practices across the API estate on Azure. Embed observability into API design as a first-class requirement. Enforce security standards appropriate to a public-facing payments API. AI-Assisted Engineering Use GitHub Copilot and Claude Opus hands-on for AI-assisted development across the .NET estate. Apply AI tooling to forward engineering - code generation and application modernization. Apply AI tooling to reverse engineering - code understanding, documentation generation and refactoring of existing applications. Integrate AI capabilities into enterprise systems through secure APIs. AI-Assisted Delivery Operate the client's existing agentic AI pipelines - configure, execute and troubleshoot pipeline runs. Review and validate AI-generated output for correctness, security and domain accuracy before it progresses. Consolidate pipeline output into structured, delivery-ready artifacts. Governance, Reporting & Collaboration Ensure designs meet enterprise standards, security requirements and scalability needs. Support solution walkthroughs with stakeholders, delivery teams and governance bodies. Maintain and present daily, weekly and monthly status reporting. Collaborate with Business Analysts, Program Managers, DevOps and Security teams. Ensure adherence to Responsible AI, security and compliance guidelines., Observability is a mandatory design requirement, not an operational afterthought, because observability data must be propagated to downstream systems. Distributed tracing designed into the API from the outset, propagated across every hop including asynchronous and queue boundaries. Correlation ID, request ID and unique transaction identifiers carried consistently across the call path and forwarded downstream. Structured logging, metrics and health instrumentation as design-time concerns. Sensitive data masking at the point of logging. Tool-specific expertise is not required. What matters is whether traceability and correlation are designed in. API Security The platform exposes a public-facing API. Standard controls are expected as a baseline of design correctness. OAuth 2.0 and OpenID Connect with appropriate flow selection; JWT validation, scope design and token lifecycle management. mTLS for partner and scheme connectivity. Object-level and function-level authorization. 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