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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building AI-enabled applications and services, with a strong focus on full-stack development using modern JavaScript/TypeScript and C#/.NET. Proficient in cloud platforms like Azure, implementing secure and scalable solutions while ensuring compliance and performance optimization.
Highest-signal resume keywords
Full-Stack DevelopmentAI-Enabled Product DeliveryAzure Cloud Platform ExpertiseC#/.NET Backend EngineeringDistributed Systems Knowledge
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
JavaScriptTypeScriptReactNext.jsC#.NETAI Model IntegrationInfrastructure as CodeAutomated Software TestingAsynchronous Processing
Soft Skills
Problem-SolvingClear CommunicationCollaborationAccountabilityAdaptability
Tools & Technologies
Azure OpenAIApplication InsightsOpenTelemetrySnowflakeCI/CD
Industry Keywords
AI CapabilitiesUser ExperienceCompliance ControlsProduction TelemetryData Protection
Tech Stack
Tools & technologiesAzureCloudDistributed SystemsJavaScriptNext.jsPythonReactSnowflakeTypeScript.NET
About the role
Key responsibilities & impact- Own solutions from discovery and architecture through implementation, phased testing, deployment, monitoring, and production support
- Build AI capabilities into real applications and workflows, including model and service integration, grounding or retrieval patterns, structured outputs, orchestration, guardrails, and fallback behavior
- Deliver intuitive web experiences, robust APIs and services, and reliable connections between application, AI, and data layers
- Create shared components, templates, reference architectures, deployment patterns, and standards for reuse across initiatives
- Define testing across development and deployment stages
- Implement automated software tests and repeatable evaluation of AI quality, reliability, latency, and failure modes
- Instrument applications for tracing AI, data, integration, and application behavior
- Diagnose issues across upstream and downstream dependencies and implement durable fixes
- Embed authentication, authorization, secrets management, data protection, auditability, compliance controls, and lineage into solution design
- Measure and improve operating cost, token consumption, model selection, retrieval strategy, caching, latency, and infrastructure use
- Report the economics of operating each solution
- Partner with UI/UX and business stakeholders to improve user outcomes and adoption
- Contribute ideas, review designs and code, share specialist knowledge, and lead challenges aligned with technical strengths
Requirements
What you’ll need- Significant professional software engineering experience, including ownership of production systems and technical decisions at Lead or Principal-caliber level
- Hands-on delivery of AI-enabled products or application features that operate in production and serve recurring business workflows
- Strong full-stack capability: modern JavaScript/TypeScript, React or Next.js, API and service development, and integration with enterprise data platforms
- Strong backend engineering experience in C#/.NET or a comparable enterprise stack
- Sound knowledge of distributed systems, asynchronous processing, and integration patterns
- Deep experience with Azure or another major cloud platform, including secure networking, identity, secrets, serverless or containerized services, CI/CD, infrastructure as code, and production telemetry
- Practical understanding of LLM application architecture, including model APIs, retrieval and grounding, prompt and context design, structured output, evaluation, monitoring, and responsible failure handling
- Ability to explain trade-offs among quality, user experience, latency, security, maintainability, and cost
- Persistent, low-ego problem-solving style; ability to work through ambiguity, seek expertise when needed, and remain accountable until issues are resolved
- Clear written and verbal communication with engineers, product partners, business stakeholders, and support teams
- Nice to have: Azure OpenAI or comparable managed model services, Azure AI capabilities, and production use of leading model providers
- Nice to have: Application Insights, OpenTelemetry, distributed tracing, AI-specific observability, or evaluation tooling
- Nice to have: Snowflake or comparable cloud data platforms
- Nice to have: Enterprise design systems, accessibility, user research, and UI/UX partnership
- Nice to have: Experience in regulated or data-sensitive environments
- Nice to have: Working proficiency in Python for AI services, evaluation, data processing, or automation
Benefits
Comp & perks- No specific benefits or compensation extras stated in the posting