Applied AI Engineer

Deriv

Deriv is an AI-first company, transforming trading through cutting-edge technology. You will play a key role in designing, developing, and deploying AI-driven solutions that power our internal tools, marketing automation, and security infrastructure.

AI is being embedded into our company DNA, across every department. For further information, please read our guide: AI at Deriv:How we re transforming fintech with AI .

Your challenges:

AI Solution Development

• Design, build, and operate agentic LLM applications with tool-use/function calling, planning, memory, and structured outputs with versioned prompts
• Implement RAG pipelines (hybrid dense+sparse retrieval, reranking); manage vector indices and the embedding lifecycle
• Integrate models with internal services and third-party APIs via tool adapters; enforce schema contracts and access controls
• Lead feature work in recommendation/ranking, content generation/editing, and workflow orchestration backed by measurable eval metrics

Security & Automation

• Build AI-driven security automations: classifiers/anomaly detectors, red-teaming harnesses, and (where appropriate) autonomous testing agents
• Implement safety & privacy controls: prompt-injection/jailbreak defenses, PII redaction, policy filtering, and auditability

Project & Task Management

• Own model/prompt/agent versioning and ship via CI/CD with canaries/A-B, rollback plans, and clear SLOs (quality, latency, cost)
• Evolve workflows: PR-based changes to prompts/configs, experiment tracking, concise design docs, and ADRs (decision records)

Quality Assurance & Code Review

• Enforce evaluation-first development: golden sets, synthetic probes, regression tests for prompts, grounding/faithfulness checks
• Review for determinism, observability, and reproducibility; address tech debt with a bias to stability and measured impact

Collaboration & Mentorship

• Partner with platform/data teams on data contracts, retrieval standards, and tenancy/access control
• Mentor peers on agent patterns, RAG, prompt engineering, and safe rollout; lead design reviews and share practical research findings

Continuous Improvement

• Benchmark and integrate new model families/tools via standardized bake-offs; report quality latency cost trade-offs
• Optimize serving with adapters/LoRA, distillation/quantization, routing/caching/speculative decoding; right-size infra for cost/perf
• Track industry and research trends; convert into pragmatic, incremental stack upgrades

Requirements:

• Strong programming skills in Python, JavaScript/TypeScript, or similar languages
• Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face)
• Hands-on experience with cloud platforms (GCP, AWS, or Azure) and containerization (Docker, Kubernetes)
• Solid understanding of security best practices and experience with security automation is a plus
• Excellent problem-solving, communication, and leadership skills
• Experience with task management and code collaboration tools (GitHub, Jira, ClickUp, etc.)
• Ability to work independently and as part of a fast-paced, collaborative team

Good to have

• Experience in AI/ML engineering, with a proven track record of delivering production-grade solutions
• Experience with marketing automation, content generation, or design systems
• Familiarity with Figma, Supabase, or similar platforms
• Contributions to open source AI/security projects
• Prior experience in a high-growth tech or fintech environment