We are looking for a Senior AI Software Engineer to join our R&D group and help design and implement our next-generation AI-driven data and intelligence platform.

This role is ideal for a senior engineer who thrives at the intersection of software engineering, data pipelines, and applied AI — someone who can bridge solid backend foundations with practical experience in modern AI systems.

You’ll lead efforts to integrate and operationalize existing open-source and commercial AI models, evaluate their performance, and optimize their cost and accuracy in production environments.

💡 What You’ll Do

• Design and build scalable data pipelines to gather, prepare, and serve data for AI workflows — including evaluation, fine-tuning, and retrieval pipelines.
• Integrate and operationalize LLMs and multimodal models, focusing on applying and adapting existing open-source or commercial models rather than building from scratch.
• Conduct error analysis, model evaluation, and cost/performance optimization to ensure production readiness and efficiency.
• Develop and maintain backend services (primarily in Java and Python) that power AI-driven features and automate data processing.
• Implement retrieval-augmented generation (RAG) and information retrieval pipelines to enhance system intelligence.
• Apply prompt engineering, validation, and A/B testing to improve system output quality.
• Collaborate with product and engineering teams to turn AI capabilities into end-user features with measurable impact.
• Stay current with emerging AI trends and tools, driving innovation and adoption across the company.

🔧 What We’re Looking For

• 7+ years of hands-on software engineering experience, including system design and production-grade development.
• B.Sc. in Computer Science or Software Engineering (M.Sc. a plus).
• Strong proficiency in Java and Python.
• Experience in cloud environments (AWS, GCP, or Azure).
• Hands-on experience with Kafka, SQL, and NoSQL databases.
• Familiarity with machine learning fundamentals, NLP, information retrieval, and RAG architectures.
• Experience building data pipelines for training, evaluation, or experimentation.
• Proven ability to conduct prompt optimization, model evaluation, and cost-aware experimentation.
• Self-driven mindset and curiosity to explore new tools, frameworks, and approaches in applied AI.

Nice to Have

• Fluency with AI‑assisted development (GitHub Copilot, Cursor, JetBrains AI) and experience defining org‑wide usage guidelines.
• Experience with multi‑model routing, tool‑use/agents, and safety classifiers/guardrails.
• Knowledge of model optimization techniques (quantization, distillation) and GPU/accelerator stacks.