Senior Software Engineer – AI Engineering

• Own a domain end to end, designing, developing, and operating backend services and core system components in production
• Set technical direction and responsibility for quality and evolution of the domain
• Lead initiatives from ideation through production by identifying opportunities, shaping solutions, coordinating contributors, and delivering outcomes
• Build and productize AI-powered features, including agents, assistants, and automation workflows
• Design agent creation and orchestration with multi-step flows, tool/function calling, state management, guardrails, and fallbacks
• Craft and refine prompts and retrieval pipelines, and evaluate quality systematically
• Collaborate with product to translate ambiguous business needs into technical solutions, scope MVPs, and connect technical decisions to user value
• Use AI coding tools in daily development while remaining accountable for shipped work
• Review human- and AI-written code for correctness, security, and maintainability
• Run proofs of concept, explore new models and tools, and turn promising approaches into team practices
• Mentor other engineers through technical challenges

• 5+ years of experience in backend software development
• A structured, methodical approach to prompt engineering and AI-assisted development, with deliberate iteration and output quality measurement
• Strong background working with relational databases and data modeling in production systems
• Hands-on experience building with LLMs in production, including model APIs, structured outputs, and creating or orchestrating agents and multi-step workflows
• Experience handling LLM failure modes, latency, and cost
• Strong background in distributed systems and system design
• Solid grasp of design patterns, algorithms, and data structures
• Experience with CI/CD pipelines and Agile methodologies
• Familiarity with cloud environments (GCP, Azure)
• English at a professional level, B2 or higher
• Advantages: strong production experience with Node.js and TypeScript
• Advantages: experience with RAG systems, including chunking strategies, embeddings, vector search, and retrieval quality tuning
• Advantages: experience with formal LLM evaluation frameworks, including eval sets, prompt regression testing, and automated quality metrics
• Advantages: multi-tenant SaaS experience or deep third-party API integration experience, including webhooks, idempotency, and rate limits
• Advantages: experience with Angular 17+ or other modern frontend frameworks