Position SummaryAs an experienced Senior Software Engineer, you will play a pivotal role in driving the design, development, and implementation of robust, scalable, secure, and modern application architecture, with deep expertise in .NET, Azure technologies, and Cosmos DB.
Beyond technical execution, this role calls for someone who takes full ownership and accountability for outcomes - running toward problems, especially in production, rather than waiting to be asked. You will understand enterprise requirements end-to-end and think several steps ahead to design solutions that stand the test of time. You will act as a hands-on architect and the team's go-to technical resource, reasoning through trade-offs with data and bringing well-communicated recommendations to the Senior Management and architecture team.
What This Role Requires- Hands-On Ownership: Personally designs, builds, reviews, troubleshoots, and supports critical components - this is a hands-on technical lead role, not a coordination-only architect position.
- Decision-Ready Judgment: Frames problems with supporting data, weighs tradeoffs, and brings a clear recommended path with business and technical impact - not just options.
- Go-To Resource: The person developers and stakeholders bring hard technical questions to - across Azure and C#/.NET - and trust to give a clear, confident answer.
- Constructive Challenge: Pushes back constructively on weak assumptions and shortcuts, balancing delivery urgency with long-term maintainability.
- Accountability: Owns outcomes beyond code complete: requirements clarity, dependencies, test readiness, release planning, observability, rollback, documentation, and hypercare.
- Force Multiplier: Builds reusable patterns, standards, templates, and runbooks, and develops secondary ownership so critical knowledge is never a single point of failure.
- AI-Forward: Actively explores, adopts, and introduces AI-driven SDLC practices - then drives their adoption across the team, validating all AI-generated output through rigorous human review and testing.
Key ResponsibilitiesEnterprise Requirements & End-to-End Ownership- Understand requirements in full enterprise context - source-of-truth decisions, upstream/downstream systems, business rules, data ownership, security, and support impact.
- Lead technical discovery into solution designs, technical stories, acceptance criteria, dependency and data mappings, exception scenarios, estimates, risks, and implementation plans.
- Own delivery from design through testing, deployment, production validation, support transition, and continuous improvement - escalating risks early with options and recommendations.
- Assess scope changes for architecture, schedule, testing, data, dependency, and operational impact before committing.
Architecture & Technical Direction- Own Azure and C#/.NET architecture, implementation, and engineering standards, aligning key architecture decisions with the Senior Manager and architecture team.
- Design cloud-native, API-led, event-driven, and data-integration solutions; document decisions, alternatives, and tradeoffs in language suited to developers, leadership, and business partners.
- Evaluate scalability, security, resiliency, performance, observability, maintainability, cost, and supportability before implementation.
- Mentor engineers through design and code reviews, pairing, and feedback; establish patterns for error handling, retries, idempotency, and reusable integration components.
Hands-On Engineering- Build industry-grade applications, APIs, microservices, and integrations using C#, .NET, and ASP.NET Core, engineered to meet sub-150ms API response targets.
- Must have strong, hands-on expertise with Azure Event Hubs, Azure Logic Apps, Azure Data Factory (ADF), and Azure Cosmos DB.
- Working knowledge of Azure Functions, App Service, Container Apps/AKS, API Management, Azure Front Door, Key Vault, Application Insights, and Azure DevOps.
- Apply strong practices for asynchronous processing, concurrency, dependency injection, authentication/authorization, data modeling, API contracts, retries, circuit breakers, idempotency, and dead-letter recovery.
- Front-end contribution (React.js, Next.js) as needed is a plus, not required - primary depth stays in backend and integration engineering.
Performance, Data & Cost Engineering- Diagnose end-to-end performance using correlated telemetry across edge, API, compute, messaging, database, and batch layers.
- Use workload evidence - latency, throughput, error/retry rates, CPU/memory, Cosmos DB RU consumption and partitioning - to guide decisions rather than guesswork.
- Tune Cosmos DB partitioning, throughput, and indexing; balance real-time and batch workloads without defaulting to capacity increases.
- Evaluate Azure cost and capacity tradeoffs, and recommend savings without weakening reliability.
DevSecOps & Release Engineering- Champion automated unit, integration, contract, regression, and performance testing with meaningful coverage as part of CI/CD quality gates.
- Build and improve Azure DevOps YAML pipelines, environment promotion, approvals, and reliable rollback strategies.
- Implement Infrastructure as Code (Bicep or equivalent) for repeatable application and platform deployments.
- Embed secure engineering practices: managed identity, secrets management, least privilege, and vulnerability remediation.
Observability, Reliability & Production Support- Design structured logging, correlation IDs, distributed tracing, metrics, and alerts that minimize noise and speed root-cause analysis.
- Define production-readiness criteria, runbooks, failure modes, and post-deployment validation.
- DR Champion: Own disaster recovery strategy end-to-end - RPO/RTO targets, failover, backup/restore, recovery automation, and periodic DR testing.
- Lead complex incident investigation with urgency, converting lessons learned into durable engineering improvements.
- Participate in an on-call rotation, remaining available to support production issues as needed.
AI-Enabled Engineering- Be a front-runner in adopting approved AI-assisted practices across the SDLC - planning, coding, testing, documentation, review, and troubleshooting.
- Validate all AI-generated output through human review, automated testing, and security controls.
- Build reusable prompts, repository instructions, and guardrails that capture team learning and promote consistent, secure AI usage.
- Track and communicate AI's impact on delivery speed, quality, and incident resolution.
Collaboration & Communication- Partner with product, QA, security, infrastructure, data, support, and onshore/offshore engineering teams.
- Lead with empathy and accountability: listen, explain reasoning, challenge respectfully, and follow through on commitments.
- Provide concise, accurate status, risk, and completion updates, keeping delivery status current.
Required Qualifications- Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- 8+ years of hands-on software engineering experience with strong depth in C#, .NET, ASP.NET Core, and Azure backend/integration services.
- Proven, end-to-end ownership of production Azure solutions - from requirements and architecture through deployment, observability, and support.
- Demonstrated expertise with cloud-native applications, microservices, event-driven architecture, and distributed-system failure handling.
- Strong, hands-on expertise with Azure Event Hubs, Azure Logic Apps, Azure Data Factory, and Azure Cosmos DB, including production troubleshooting and performance optimization.
- Solid experience with automated testing, Azure DevOps CI/CD, Git, Infrastructure as Code, containers, and observability tooling.
- Demonstrated ability to mentor developers, conduct design/code reviews, communicate tradeoffs, and lead through ambiguity.
- Practical, responsible experience using AI development tools, including output validation and data protection.
Preferred Qualifications- Microsoft Certified: Azure Developer Associate; Azure Solutions Architect Expert strongly preferred.
- Experience with disaster recovery, high-availability architecture, distributed tracing, and production on-call support.
- Cosmos DB partitioning/RU optimization, Azure performance engineering, and FinOps practices.
- Experience standardizing AI-assisted engineering workflows or reusable development automation.
- Experience in retail, distribution, supply chain, or heavy-duty aftermarket domains.
Success Measures- Risks, dependencies, and non-functional requirements are surfaced before development and QA.
- Solutions reach production with automated tests, observability, documented support ownership, and validated rollback/recovery.
- Technical debt is prevented where practical, or explicitly documented and bounded when intentionally accepted.
- Develops clean designs, and reusable engineering assets grow over time.
- AI-assisted development shows measurable improvement while maintaining human validation and quality.
