LanguageWire

AI Engineer

• You will help improve our existing ML-based products and build new features and services using LLMs.
• A core part of the role is context engineering — designing the right inputs, retrieval strategies, and prompt structures to get the best possible output from LLMs in production.
• You'll also contribute to our software engineering efforts when needed, bridging the gap between ML and software engineering on the team.
• You will work in the Machine Learning Team, where we build LanguageWire's machine translation (MT) and adjacent services to monitor and predict its performance.
• The team consists of ML Engineers, Analytics Engineers, and Full Stack Software Engineers.
• You'll collaborate across these disciplines daily, and we value people who can move fluidly between ML experimentation and production engineering.
• You'll report to the team leader.

Full-stack Engineer

• 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.

Full Stack Engineer, AI Tools & Integrations

• Take end-to-end ownership of features and services: from design and coding to deployment, monitoring, and maintenance (“You build it, you run it”).
• Collaborate with product managers and designers to shape solutions that solve real user problems.
• Modernize and expand our front end while contributing to backend services and databases.
• Contribute to the architecture, design, and implementation of new product capabilities.
• Set up and improve CI/CD pipelines to deliver frequently and with confidence.
• Ensure quality through testing (TDD/BDD), code reviews, and proactive issue prevention.
• Apply best practices in DevOps, Automation, and Operational Excellence.
• Share knowledge with the team.

Full Stack Engineer

• As Engineering Team Lead, you'll take ownership of an existing team — hiring new engineers, developing the people you have, and raising the bar on how the team works.
• Together you discover customer problems worth solving, decide what to build, and own the outcome. Your team is responsible for the full development lifecycle — you build it, you run it.
• You'll join an existing team in the Technology department, working alongside 6 other teams in a distributed, international setup.
• Your team develops and maintains some of the most critical components that sustain our business such as authentication/authorization, object/file storage, notifications (chat, email, SMS), back office integrations (CRM & ERP), reporting and AI Agents integration into our business workflows.
• You'll report to the Director of Engineering and work closely with five other Tech Leads.
• Co-driving the product. Together with your PM, you own the product. You bring technical insight into what's possible, shape the solution, and take shared responsibility for outcomes — not just delivery.
• Leading and growing your team. Hiring well, developing people's skills, and creating an environment where senior engineers and newer talent both thrive.
• Driving engineering excellence. Raising the bar on CI/CD, infrastructure as code, automated testing, observability, and everything else that lets a team ship confidently and often.
• Staying hands-on. Contributing to the codebase through implementation and code reviews. You lead by example.
• Designing scalable solutions. Architecting cloud-native services and integrating AI agents into business workflows.
• Raising the bar beyond your team. Collaborating with fellow Tech Leads and senior leadership to improve engineering maturity across the organization — processes, practices, and culture.