Space Executive

About the Company

Space Executive is a multi-disciplinary, award-winning international executive search and selection recruitment agency. With offices in Singapore, Hong Kong and London the company specialises in recruiting senior management and executive-level personnel.

We work with Multinationals, Financial Services, Technology, Healthcare, FMCG, Consultancy, Insurance, Venture Capital & High Growth or Equity-Backed companies across Leadership and General Management, Technology and Change Management, Chief Operating Officer and Governance, Management Consultancy and Sales & Marketing positions.

Space Executive has been recognised for its exceptional work and service delivery in recruitment; its awards include Best Places to Work in 2019, Recruitment International Best Newcomer 2016, Global Recruiter Asia Pacific Gold Award 2016, and was ranked Most Socially Engaged Staffing Agency in both 2016 and 2017 by LinkedIn.

Our clients include Sequoia Capital, Airwallex, Ant Group, Credit Suisse, Standard Chartered, Goldman Sachs, Lazada, Dyson, Diageo, PWC, William Grant, YUM Brands, WeWork, Allianz and Johnson & Johnson; they choose Space Executive because of our ability to recognise that Your Space is Our Space.

Listed Jobs

Company Name

Space Executive

Job Title

AI Research Engineer

Job Description

**Job title:** AI Research Engineer **Role Summary:** Design, develop, and evaluate advanced AI agents that enhance threat detection, vulnerability triage, and incident response for a next‑generation cybersecurity platform. Translate cutting‑edge AI research—particularly reinforcement learning and large language models—into production‑ready solutions that scale across enterprise and defense environments. **Expectations:** * 4+ years engineering experience in production settings. * Demonstrated AI/ML research background (academic, open‑source, or startup). * Proficiency in Python, PyTorch, and TypeScript. * Deep knowledge of LLMs, transformer architectures, and foundational models. * Familiarity with reinforcement learning. * Startup‑style ownership mentality, resourcefulness, and a drive to build high‑impact technology. **Key Responsibilities:** 1. Conceptualize and build new AI agents tailored to security workflows, improving autonomy and effectiveness. 2. Optimize existing agents for performance, scalability, and robustness. 3. Create evaluation frameworks to measure agent impact on security metrics. 4. Apply state‑of‑the‑art AI methods—RL, LLMs, transformers—to novel cybersecurity challenges. 5. Monitor AI research trends and translate emerging techniques into practical product features. 6. Collaborate cross‑functionally with software teams to integrate AI solutions into the platform stack. 7. Shape and lead the company’s research agenda, influencing product strategy. **Required Skills:** * Python programming (deep learning, data pipelines). * PyTorch expertise (model training, inference). * TypeScript for integration/testing. * In‑depth understanding of LLMs, transformers, and foundational models. * Knowledge of reinforcement learning principles and frameworks. * Strong problem‑solving, analytical, and communication skills. * Experience deploying AI solutions to production environments. **Required Education & Certifications:** * Bachelor’s degree (or higher) in Computer Science, Electrical Engineering, Applied Mathematics, or a related field. * No mandatory certifications; relevant AI/ML coursework or proven research contributions are preferred.

San francisco bay, United states

Hybrid

Junior

25-11-2025

Company Name

Space Executive

Job Title

Artificial Intelligence Engineer

Job Description

Job Title: Artificial Intelligence Engineer Role Summary: Design, develop, and deploy enterprise‑grade AI agents that integrate large language models, retrieval‑augmented generation, and agentic workflows. Leverage data science, machine learning, and MLOps expertise to transform complex business challenges into scalable AI solutions for high‑value clients. Expectations: - Deep understanding of machine learning, data science, and modern AI technologies (LLMs, RAG, LangChain, co‑pilot frameworks, agentic systems). - Proven ability to translate stakeholder requirements into technical AI architectures. - Continuous learning mindset to keep pace with rapidly evolving AI tools and practices. - Strong communication skills to collaborate with cross‑functional teams and executive stakeholders. Key Responsibilities: - Architect and implement custom AI agents tailored to enterprise client needs. - Integrate LLMs, RAG pipelines, and agentic workflows with existing data infrastructure. - Design end‑to‑end ML pipelines, including data preprocessing, model training, evaluation, and deployment. - Ensure model performance, scalability, and robustness in production environments. - Conduct technical workshops and demos to explain AI solutions to business users. - Participate in MLOps practices: CI/CD, monitoring, and continuous improvement of models. - Collaborate with data engineers, product managers, and domain experts to refine AI use cases. Required Skills: - Programming: Python, libraries (PyTorch/TensorFlow, Hugging Face, LangChain, Ray, etc.). - Machine Learning: supervised/unsupervised learning, model evaluation, hyperparameter tuning. - AI Platforms: OpenAI, Anthropic, Azure OpenAI, Google Vertex AI or equivalent. - Retrieval‑Augmented Generation and RAG pipelines. - Agentic workflows and co‑pilot integration. - MLOps: Docker, Kubernetes, CI/CD, monitoring tools. - Data handling: SQL, NoSQL, data pipelines (Airflow, Prefect). - Stakeholder communication and requirement elicitation. - Problem‑solving, analytical thinking, and rapid prototyping. Required Education & Certifications: - Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. - Professional certifications (e.g., Google Cloud Professional ML Engineer, AWS Certified Machine Learning – Specialty) are a plus.

London, United kingdom

Hybrid

06-01-2026