Web & AI SaaS Engineer

Description
About Us

We 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.