About this role
About UsWe are a fast-growing company specializing in value-added solutions for ERP platforms, with a strong focus on SAP Business One and other mid-market ERP systems. Our solutions help ERP users extend functionality, improve productivity, and drive digital transformation.
About the Role
We’re hiring a Web & AI SaaS Engineer to build and ship modern web-based SaaS solutions that embed LLM-powered capabilities into real business workflows. You’ll deliver secure, scalable, production-ready experiences across UI, APIs, data, and AI orchestration using a modern .NET web stack and cloud fundamentals.
This role is for someone who combines SaaS product thinking (security, scaling, observability, tenant-aware design) with practical AI engineering (agents/multi-agent workflows, RAG, and NLP-to-SQL).
Responsibilities
Build web product features using Blazor Server / Razor and modern web patterns (routing, state, forms, validation, accessibility). Design and implement backend services and REST APIs in C#/.NET 10 (versioning, pagination, idempotency, error contracts). Implement LLM-powered capabilities using strong system instruction patterns, context management, and tool/function calling. Build and operate RAG pipelines end-to-end: ingestion, chunking, embeddings, retrieval, reranking/grounding, and quality monitoring. Design agent and multi-agent workflows (planner/executor patterns, tool routing, guardrails, memory/context strategies, evaluation). Implement NLP-to-SQL and structured query generation with safety controls (schema awareness, constrained generation, permission checks, validation). Apply SaaS fundamentals: tenant-aware design, configuration, feature flags, usage metering, rate limiting, and secure customer isolation. Integrate with external services (identity providers, third-party APIs) using clean abstraction layers. Own production readiness: performance, caching, resiliency (timeouts/retries/circuit breakers), and reliable background processing. Implement observability: structured logs, metrics, traces, dashboards, and actionable alerts. Collaborate in Agile/Scrum, track work in Jira, and contribute via code reviews and standards.
Required Skills & Experience
Strong software engineering fundamentals and architecture skills (system design, modularity, scalability, code quality, testing). Strong experience building web applications with C#/.NET (Blazor preferred). Solid understanding of SaaS architecture and web delivery concerns (security, scaling, deployments, monitoring). Strong knowledge of API design and integration patterns (OAuth/JWT, RBAC, CORS, webhooks, API gateways). Hands-on experience with the OpenAI API and the OpenAI developer platform (model selection, structured outputs, streaming, rate limits, tooling). Hands-on experience with Google Gemini APIs and/or Vertex AI (model invocation, safety controls, deployment/ops basics). Strong practical knowledge of LLM hyperparameters and behavior tuning (temperature, top_p, max tokens, penalties, determinism considerations). Experience building agents/multi-agent systems, including orchestration, guardrails, and evaluation. Experience implementing RAG and retrieval strategies. Experience with NLP-to-SQL or text-to-structured-query approaches, including safety and correctness constraints. Strong database fundamentals with relational databases (schema design, SQL, indexing, query optimization). Comfortable shipping iteratively in an Agile environment using Jira.
Nice-to-Have
Experience using AI coding agents (e.g., Claude Code, Codex) to augment productivity, accelerate implementation, and create/maintain high-quality documentation. Experience with identity providers (Auth0/Okta/Azure AD), SSO/SAML/OIDC. Experience with vector search / vector databases (pgvector, OpenSearch, Pinecone, Qdrant, etc.). Experience with background jobs, queues, caching (Redis), and real-time updates. CI/CD experience and Infrastructure-as-Code familiarity (GitHub Actions/Azure DevOps, Terraform/CDK). Experience with AI evaluation/testing: golden datasets, regression tests for prompts/agents, offline scoring, and tracing. Experience with ERPs.
Typical Tech Stack
.NET 10, C#, REST Blazor Server, Razor JavaScript/TypeScript for advanced UI needs and integrations AWS and cloud fundamentals; OpenAI developer platform + Google Gemini / Vertex AI Agent orchestration patterns, RAG, embeddings, retrieval, evaluation/monitoring Relational databases (SQL Server/Postgres/etc.)
What Success Looks Like
You ship web experiences that are fast, secure, and production-ready. AI features are measurable, reliable, and monitored, with clear guardrails and fallbacks. SaaS foundations are solid (tenant readiness, observability, deployment hygiene, security posture). Integrations and AI orchestration are cleanly abstracted for easy evolution.