Full Stack Engineer, LanguageWire

• Strong backend experience: C#, .NET Core / .NET 6+, ASP.NET Web API, microservices
• Solid experience with relational databases (MSSQL and/or PostgreSQL), query design, schema design, performance
• Proven ability to design and build REST APIs and integrate with third-party services and webhooks
• Familiarity with async programming, event-driven architecture, and message queues (e.g., Azure Service Bus, RabbitMQ)
• Some frontend exposure (Vue.js and/or TypeScript), enough to contribute when needed, but the focus here is backend
• Practical understanding of LLM APIs (Anthropic, OpenAI, Azure OpenAI), calling them, managing context, handling responses
• Familiarity with designing or consuming tool/function calling schemas, defining what an agent can invoke and how
• Familiarity with MCP (Model Context Protocol) or similar agent-tool integration patterns (or eagerness to learn)
• Understanding of security and authentication for exposed tool APIs (OAuth 2.0, API keys, rate limiting, input validation)
• Observability mindset: logging, tracing, and monitoring tool invocations and agent interactions
• A product mindset: you care about solving real business problems, not just completing tickets
• Comfortable working with domain experts (non-technical stakeholders) to identify automation opportunities and translate them into technical solutions
• Strong communication skills, English fluency required
• Agile, collaborative, and opinionated in a constructive way

Desirable

• As a Full Stack Engineer in the Core Platform Team, you’ll be at the forefront of how LanguageWire puts AI to work across the business
• You won’t be training models or doing data science, you’ll be building the tools, services, and workflows that let AI agents actually do things: query internal systems, interact with third-party APIs, automate cross-department workflows, and solve real business problems end-to-end
• You’ll own the design and delivery of backend-heavy services that expose well-defined, reliable tool interfaces consumed by AI agents
• You’ll collaborate with product managers, domain experts from across the company, and fellow engineers to identify pain points and turn them into agentic solutions
• You'll join the Core Platform Team, one of the foundational engineering teams at LanguageWire
• The team owns and operates 12 microservices that underpin the entire organisation, covering file storage, authentication, notifications, email delivery, and integrations with our ERP and CRM systems, among others
• These are the services every other team depends on
• As LanguageWire invests in AI, the Core Platform Team is taking on a new function: building the tools and integrations that allow AI agents to interact with our services and automate workflows across departments
• You'll be at the forefront of that expansion, turning the platform's capabilities into reliable, well-defined interfaces that AI agents can act on
• We value outcomes over output, shared ownership over silos, and continuous delivery over long release cycles
• Our stack is built on .NET microservices, Azure, and modern API patterns
• Design and build AI agent tools: Create backend services and APIs that AI agents can invoke to query data, trigger workflows, and interact with internal and external systems
• Integrate with existing services and APIs: Connect agent tooling to LanguageWire’s internal platform APIs, third-party services, and databases
• Define tool schemas and contracts: Design clear, well-documented tool interfaces (function schemas, OpenAPI specs, MCP server definitions) that LLMs and orchestration layers can reliably consume
• Build agentic features and workflows: Implement end-to-end automated workflows where AI agents solve specific business cases across departments, from operations and finance to sales and project management
• Own your services end-to-end: From architecture and coding to deployment, monitoring, and maintenance (“You build it, you run it”)
• Contribute to backend services and data layers: Extend existing .NET microservices and databases to expose the capabilities needed by AI tools
• Set up and improve CI/CD pipelines to ship reliably and frequently
• Apply DevOps and Operational Excellence best practices to ensure agent tools are observable, resilient, and secure
• Share knowledge with the team and help define how we build AI-powered products
• In one year, you’ll know you were successful if…
• AI agents are actively solving real problems across multiple departments using tools you built
• Internal teams are saving meaningful time through automated workflows you’ve designed and shipped
• Your tool APIs are robust, well-documented, and trusted by both engineers and the AI orchestration layer
• You’re recognized as a go-to person for backend architecture and AI tool integration within the team