Senior AI Engineer
New
EuropeFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- PythonRESTful APIsLLM
Requirements
- Strong professional experience as a Senior AI Engineer, Senior ML Engineer, or similarly senior-level software engineer building production AI systems.
- Strong hands-on experience with Python in real production environments.
- Understanding of building AI-enabled systems that go beyond prototypes and function reliably as part of commercial software products.
- Strong understanding of AI workflow design, orchestration, service integration, backend architecture, and the surrounding engineering systems required to make AI useful in production.
- Experience working with large language models, intelligent automation systems, or AI-powered pipelines in real business applications.
- Strong knowledge of APIs, asynchronous workflows, backend services, and multi-step processing systems.
- Expertise in designing, implementing, and maintaining AI pipelines for tasks such as summarization, extraction, classification, scoring, or workflow automation.
- Ability to balance experimentation with engineering discipline and convert promising ideas into scalable, maintainable systems.
- Expertise in debugging and troubleshooting across AI behavior, workflow failures, service interactions, and production bottlenecks.
- Ability to operate independently, make sound technical decisions, and contribute effectively in an environment with evolving priorities and limited bureaucracy.
Responsibilities
- Design, build, and improve production-grade AI capabilities that support real business workflows, including transcription, summarization, data extraction, classification, scoring, orchestration, and agent-driven execution flows.
- Develop and maintain AI-related backend services and processing pipelines using Python, with a focus on reliability, scalability, observability, and production performance.
- Help architect and evolve the platform’s AI orchestration layer, including the logic, control mechanisms, and deterministic infrastructure required for AI systems to operate safely and effectively in production.
- Work closely with founders and engineering leadership to translate product goals into scalable AI-enabled systems that can support high usage volume and rapid feature evolution.
- Build and improve structured workflows that connect AI services with operational systems, internal tools, customer-facing platform features, and downstream business logic.
- Take ownership of substantial technical areas and contribute meaningfully to architectural decisions involving orchestration, tool execution, workflow control, quality evaluation, and scaling strategy.
- Contribute to the development of agentic workflow systems where AI capabilities must operate within controlled, deterministic environments and interact with tools, data, and structured business rules.
- Improve system quality across latency, throughput, output consistency, observability, failure handling, and cost efficiency.
- Evaluate and apply modern AI tooling, frameworks, and workflow patterns where appropriate, while also being comfortable building pragmatic internal solutions from scratch when greater control or performance is needed.
- Collaborate with backend, data, and full-stack engineers to ensure AI functionality is integrated cleanly into the broader platform and product experience.
- Help establish sound engineering practices for AI development, including production-readiness, testing discipline, instrumentation, operational monitoring, and iterative improvement.
- Participate in a fast-moving product and engineering environment where new ideas are explored quickly, and high-quality solutions are continuously pushed into production.
- Take ownership of a meaningful AI workflow area from design through delivery
- Identifying weak points in an AI pipeline and proposing practical improvements
- Work effectively in ambiguous problem spaces where requirements are not fully fixed.
- Help shape technical direction rather than simply following instructions, contribute production judgment around stability, observability, and scalability.
- Work directly with founders and senior engineers in a high-trust, high-autonomy environment.
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