Engineering - Software Engineer (AI & Agentic Solutions)
Indexed description
We're looking for a Software Engineer who wants to build enterprise features using AI and agentic patterns. This is a hands-on product engineering role where you'll work inside our .NET/Azure stack to help build and ship AI-powered capabilities across Aline's product suite.
You'll use large language models, agent orchestration frameworks, and retrieval-augmented generation as tools in your engineering toolkit — the same way you'd use a message broker or a search index. You won't be doing this alone — you'll be working alongside senior engineers and leads who will help you grow — but you'll have real ownership of features from day one. This role reports into Aline's engineering organization and works cross-functionally with product, QA, and customer-facing teams.
Responsibilities
Build AI-Powered Product Features
- 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.
Required
- 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.
- 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.
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