SENIOR TECHNICAL LEAD

Key Responsibilities

AI-Enabled Engineering

• Use Claude agents as a primary development partner across the SDLC:
1. Design: translate requirements into technical designs, evaluate approaches, and draft architecture with agent assistance.
2. Code: generate, refactor, and document code, keeping the engineer accountable for correctness and quality.
3. Unit testing: create and maintain unit tests with strong coverage.
4. Functional testing: author and run Playwright end-to-end and functional tests.
5. PR review: use Claude agents to assist with pull request reviews, catching defects, style issues, and risks before merge.
• Apply best practices for the responsible and secure use of AI agents, including reviewing and validating all agent-generated output before it ships.
• Continuously refine prompts, context, and agent workflows to improve reliability and results.

Technical Delivery

• Design and deliver scalable, secure, cloud-native solutions using:
1. .NET (C#, ASP.NET Core, APIs)
2. Azure Cloud Services

? Contribute to microservices, APIs, and distributed systems, with attention to sound design patterns.

DevOps & Azure Ecosystem

• Build and maintain CI/CD pipelines using Azure DevOps (YAML pipelines).
• Apply best practices in:
1. Automated testing (unit, integration, functional/Playwright)
2. Continuous delivery and deployment
3. Infrastructure as Code (Terraform Enterprise)

? Support integration across App Gateway, APIM, and backend services.

Observability & Operational Excellence

• Implement monitoring and observability using:
1. Azure Monitor, Application Insights, Log Analytics
2. Datadog

? Help identify and resolve performance, reliability, and scalability issues.

? Assess the impact of platform updates (e.g., Microsoft releases) on applications.

Business Value Enablement

• Partner with Product Owners and stakeholders to translate requirements into working, tested solutions aligned to business outcomes.
• Move from task execution toward outcome ownership.

Collaboration

• Collaborate with Architecture, Security, Infrastructure, and Network teams.
• Contribute to team decisions on cloud, DevOps, and AI adoption.

Expected Outcomes

• Increased productivity through agentic AI development with Claude
• Faster time-to-market via optimized CI/CD pipelines
• High-quality, well-tested code with strong unit and Playwright functional coverage
• Improved application reliability and observability
• Stronger engineering ownership and accountability
• Measurable business value delivery from engineering efforts

Required Qualifications

• 5+ years of overall software engineering experience.
• 1+ years of AI engineering experience.
1. Solid expertise in:
1. C#, ASP.NET Core, API development.
2. SQL Server.

? Hands-on experience with:

1. Azure Cloud (App Services, APIM, Data Services).
2. Azure DevOps (Boards, Repos, Pipelines).
3. Ci/CD and automated testing.
4. Familiarity with AI-assisted or agentic development workflows.

Preferred Qualifications

• Hands-on experience with Claude agents (or similar agentic AI coding tools)

? Experience building AI-assisted engineering workflows across design, coding, and testing.

• Experience with Playwright for functional/end-to-end testing.
1. Knowledge of:
1. Terraform (Infrastructure as Code).
2. Microservices architecture & design patterns.
3. Azure Data Factory, Synapse, Databricks.

? Familiarity with observability tools (Datadog preferred)

? Azure certifications (e.g., Azure Developer Associate).

Key Competencies

• Strong problem-solving and systems thinking.
• Ability to direct and verify AI agents—strong judgment about when to trust, correct, or override agent output.

? Ability to translate technology into business value.

• Excellent communication and collaboration skills.
• Growth mindset and passion for continuous learning and innovation.

? Ability to thrive in a fast-paced, Agile environment.

What Makes This Role Different

This is not a traditional software engineering role. You will:

• Work agent-first, using Claude to design, code, test, and review.
• Work smarter, not harder, letting agents handle toil while you own direction and quality.
• Drive a culture of ownership, automation, and innovation.

? Directly impact business outcomes, not just code delivery