Engineering - Software Engineer (AI & Agentic Solutions)

• Help build multi-step agent workflows for enterprise use cases — using Semantic Kernel, Claude Agent SDK, LangGraph, or comparable frameworks. ·
• Learn and apply orchestration patterns: planner/executor, tool-calling, human-in-the-loop, and safe fallback chains.
• Build tool interfaces and APIs that connect agent capabilities to production systems.
• Implement state management, retry logic, and error handling for agent workflows under guidance from senior engineers.

• Write clean, testable C# / .NET code that integrates AI capabilities into Aline's existing services and APIs.
• Work within Aline's Azure infrastructure — Azure App Services, Azure Functions
• Contribute to CI/CD pipelines in GitHub for AI-enabled services.
• Participate in code reviews, architecture discussions, and sprint ceremonies.
• Help build evaluation harnesses — golden test sets, regression suites, and LLM-as-judge pipelines — that validate AI feature behavior before release.
• Work within Aline's AI-assisted Development Lifecycle (ADLC) — using AI-powered tooling to accelerate code generation, testing, code review, and feature delivery.

• Implement guardrails, content filtering, and input validation to ensure AI features behave safely and predictably in a senior living / healthcare-adjacent environment.
• Follow multi-tenant data isolation patterns — AI features must respect company and community-level data boundaries.
• Develop awareness of compliance requirements relevant to the senior care industry (SOC 2, HIPAA, data residency) and apply them in your work.

• 4–6 years of software engineering experience (or a strong recent graduate with demonstrable project, internship, or research experience at equivalent depth) — backend or full-stack, building and shipping applications.
• Proficiency in C# and .NET (ASP.NET Core, Web API, dependency injection, async patterns).
• Familiarity with Azure — App Services, Azure Functions. Exposure to Cosmos DB, Azure SQL, or Azure AI services is a plus. · Experience using LLMs in application code — calling Azure OpenAI or Anthropic APIs, managing prompts, parsing structured responses. This can include personal projects, hackathons, or professional work.
• Solid fundamentals in SQL and relational databases — PostgreSQL, SQL Server, or similar.
• Familiarity with REST API design, JSON serialization, and service-to-service integration patterns.
• Git version control and comfort working in Agile/Scrum teams.

• Experience with an agent orchestration framework: Semantic Kernel, Claude Agent SDK, LangGraph, AutoGen, or CrewAI.
• Experience with RAG architecture — embedding models, vector search (pgvector, Azure AI Search), chunking strategies, reranking.
• Exposure to MCP (Model Context Protocol) or building typed tool interfaces for LLM agents.
• Experience building evaluation and testing pipelines for AI features — golden sets, LLM-as-judge, A/B or shadow evaluation.
• Familiarity with observability and monitoring — DataDog, Application Insights, or similar — for AI-enabled services.
• Understanding of multi-tenant SaaS architecture and data isolation patterns.
• Awareness of AI safety and compliance considerations: prompt injection mitigation, content filtering, PII handling, audit logging.
• Azure AI certifications (AI-102, AI-103) or equivalent demonstrated knowledge.

Beyond the Requirements

• You think of LLMs as a tool in your engineering stack, not as the product itself. You're curious about reliability, latency, cost, and user experience — not just model capability.
• You're willing to work across the stack when needed — backend services, API layers, and lightweight frontend integration — and eager to learn what you don't know yet.
• You communicate clearly and aren't afraid to ask questions. You can explain what you're building and why to engineers, product managers, and customers.
• You're self-motivated, detail-oriented, and comfortable operating in a fast-moving environment where the playbook is still being written.
• You have a genuine interest in improving outcomes in senior care through responsible, production-grade AI.

This job description is intended as a summary of the primary responsibilities of and qualifications for this position.

The job description is not intended as inclusive of all duties an individual in this position might be asked to perform or of all qualifications that may be required either now or in the future.