Engineering - Software Engineer (AI & Agentic Solutions)

Summary

Aline provides an all-in-one technology platform for senior living communities, supporting sales, marketing, operations, and resident and family engagement. The Software Engineer will build and ship AI-powered enterprise features within Aline’s .NET and Azure stack, contributing to LLM integrations, agentic workflows, RAG pipelines, production software, testing, compliance, and reliability.

Responsibilities

• Help design and implement AI-assisted features across Aline's product suite — help doc search, onboarding workflows, intelligent notifications, content generation, and conversational interfaces
• Integrate LLM capabilities (Azure OpenAI, Anthropic Claude) into existing .NET services via API, SDK, or agent framework
• Contribute to retrieval-augmented generation (RAG) pipelines that ground AI responses in Aline's customer data — using PostgreSQL, pgvector, or Azure AI Search
• Write and iterate on prompts, manage context windows, and validate AI responses for production features
• 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

Skills

• • 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

Qualifications

Must Haves

• • 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

Nice to Haves

• • 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