Senior Software Engineer — AI Engineering.

Accountabilities

• Own the design, development, deployment, and ongoing operation of backend services and core system components, ensuring their quality, reliability, and continued evolution.

• Lead initiatives from ideation through production by identifying opportunities, defining technical solutions, coordinating contributors, and driving delivery.

• Build and productize AI-powered features, including intelligent agents, assistants, and automation workflows that customers can rely on in production.

• Design agent creation and orchestration systems, including multi-step workflows, tool and function calling, state management, guardrails, and fallback mechanisms for model failures.

• Develop, refine, and systematically evaluate prompts and retrieval pipelines, using measurable results rather than intuition alone to assess quality.

• Partner closely with Product to translate ambiguous business needs into practical technical solutions, define appropriate minimum viable products (MVPs), and connect engineering decisions to user and business value.

• Use AI-assisted coding tools effectively in daily development while maintaining full engineering accountability for the correctness, security, and maintainability of shipped code.

• Review both human-written and AI-generated code, identifying potential issues and maintaining high standards for software quality and long-term sustainability.

• Explore new AI models, tools, and development approaches through proofs of concept, then integrate successful innovations into established engineering practices.

• Apply strong system design principles to build scalable, reliable backend systems and evolve the technical architecture of the assigned domain.

• Mentor other engineers, provide technical guidance, and contribute to a collaborative culture of continuous learning and improvement.

Requirements

• At least 5 years of professional experience in backend software development.

• Hands-on experience building and deploying production-grade applications using large language models (LLMs), including model APIs, structured outputs, agents, and multi-step workflows.

• Experience managing real-world AI challenges, including failure handling, latency, cost optimization, and the reliability of AI-powered features.

• A structured, methodical approach to prompt engineering and AI-assisted development, with a willingness to iterate deliberately and measure output quality.

• Strong experience with relational databases and data modeling in production environments.

• Solid knowledge of distributed systems, system design, software design patterns, algorithms, and data structures.

• Experience working with continuous integration and continuous delivery (CI/CD) pipelines and Agile development methodologies.

• Familiarity with cloud environments such as Google Cloud Platform (GCP) or Microsoft Azure, along with the ability and willingness to expand technical expertise as needed.

• Strong ownership and leadership skills, with the ability to take initiative, navigate ambiguity, establish clarity, and move projects forward independently.

• Excellent communication and collaboration skills, including the ability to explain technical trade-offs, justify architectural decisions, and work effectively with product managers and senior stakeholders.

• A business-oriented mindset, with the ability to look beyond task specifications and prioritize solutions that address genuine customer and business needs.

• Curiosity, creativity, and a proactive approach to learning new technologies, exploring unconventional solutions, and bringing ideas into production.

• A collaborative attitude and commitment to building high-quality software as part of a team.

• Professional English proficiency at B2 level or higher.

Preferred qualifications:

• Strong production experience with Node.js and TypeScript.

• Experience building retrieval-augmented generation (RAG) systems, including chunking strategies, embeddings, vector search, and retrieval quality optimization.

• Familiarity with formal LLM evaluation frameworks, including evaluation datasets, prompt regression testing, and automated quality metrics.

• Experience with multi-tenant SaaS platforms or complex third-party API integrations involving webhooks, idempotency, and rate limits.

• Experience with Angular 17+ or other modern frontend frameworks, and an interest in contributing beyond backend engineering.

Benefits

• Salary and compensation details are not specified in the provided job description.

• Opportunities to take ownership of significant AI engineering initiatives from concept through production.

• A senior individual contributor position with technical leadership, architectural decision-making, and mentoring responsibilities.

• Opportunities to experiment with emerging AI models, tools, and engineering approaches and bring successful innovations into production.

• Close collaboration with Product and Engineering teams to influence technical direction and deliver customer-focused solutions.

• A technically challenging environment focused on applied AI, backend systems, and continuous innovation.