Agentic AI Engineer

Bitdeer is a world-leading technology company for Bitcoin mining and AI cloud.

Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers. Apart from designing industry-leading ASIC chips and manufacturing mining rigs, the Group handles complex processes involved in computing across the value chain. This includes equipment procurement, transport logistics, datacenter design and construction, equipment management, and network and facility operations. Bitdeer also offers advanced cloud capabilities to customers with a high demand for artificial intelligence.

Headquartered in Singapore, Bitdeer operates globally with a diversified 3 GW energy portfolio, and deploys Bitcoin mining and HPC datacenters in the United States, Bhutan, Norway, Canada, Malaysia, and Ethiopia.

• →Design and build scalable multi-agent architectures (planners, executors, judges) to automate end-to-end NeoCloud engineering and business workflows.
• →Integrate AI agents with internal services, SaaS platforms, and APIs to autonomously trigger infrastructure actions, such as node cordoning, checkpointing, and hardware remediation.
• →Develop autonomous agents that can generate code, refactor software, and analyze telemetry to self-correct system issues in real-time.
• →Architect short-term and long-term memory systems for agents, ensuring continuity across long-running infrastructure tasks using protocols like the Model Context Protocol (MCP).
• →Implement advanced Retrieval-Augmented Generation (RAG) pipelines to ground agent decisions in reliable data from our telemetry and observability stacks.
• →Enforce rigorous evaluation and guardrails via "LLM-as-a-Judge" mechanisms, ensuring agent performance, reliability, and security compliance.
• →Establish company-wide Harness engineering practices to automate the deployment, governance, and lifecycle management of agentic systems, leveraging CI/CD and feature flagging.
• →Collaborate with Kubernetes and Infrastructure Engineering teams to integrate autonomous agents into the platform's control plane for proactive, self-optimizing resilience.

• →A culture that values authenticity and diversity of thoughts and backgrounds;
• →An inclusive and respectable environment with open workspaces and exciting start-up spirit;
• →Fast-growing company with the chance to network with industrial pioneers and enthusiasts;
• →Ability to contribute directly and make an impact on the future of the digital asset industry;
• →Involvement in new projects, developing processes/systems;
• →Personal accountability, autonomy, fast growth, and learning opportunities;
• →Attractive welfare benefits and developmental opportunities such as training and mentoring.

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Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, colour, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.

#LI-ST1

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
• Minimum 6+ years of software engineering experience, with deep expertise in production-grade Python and TypeScript.
• Extensive experience with modern agentic frameworks (e.g., LangGraph, CrewAI) and working with frontier Large Language Models (OpenAI, Anthropic Claude).
• Proven track record of designing complex systems that map ambiguous business processes into robust, reusable AI logic and patterns.
• Experience deploying AI features into managed runtimes and cloud-native environments (AWS, Azure, GCP, or private clouds).
• Familiarity with Kubernetes internals, infrastructure automation, and CI/CD pipelines (e.g., Jenkins, GitHub Actions, Harness).
• Strong understanding of distributed systems, telemetry, observability stacks (Prometheus, OpenTelemetry), and hardware-level metrics
• Demonstrated leadership in bridging the gap between traditional software engineering and autonomous AI, with excellent communication skills.
• Ability to work in a high-velocity, cross-functional engineering environment with a focus on delivering scalable, reliable software.