Agentic AI Engineer
Bitdeer is a technology company providing Bitcoin mining solutions.
Funding history
Investors
Projects
About Bitdeer
Bitdeer provides full-spectrum Bitcoin mining and high-performance computing solutions, including SEALMINER mining equipment, Minerbase cooling containers, cloud mining, co-mining, mining management applications, mining rights marketplaces, and large-scale data center operations. The company also offers AI cloud infrastructure with GPU computing, model training and deployment capabilities, and turnkey AI data center solutions for enterprise customers and developers. Bitdeer is headquartered in Singapore and operates globally.
Skills
About the Role
You will design multi-agent systems, connect agents to internal services and infrastructure APIs, build coding and self-correcting agents, architect agent memory, implement RAG pipelines and evaluation guardrails, automate agent deployment and governance, and integrate autonomous capabilities into Kubernetes control planes.
Requirements
- Bachelor's or master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field
- At least 6 years of software engineering experience
- Deep expertise in production-grade Python and TypeScript
- Extensive experience with agentic frameworks such as LangGraph and CrewAI
- Experience working with frontier large language models such as OpenAI and Anthropic Claude
- Experience mapping ambiguous business processes into reusable AI logic and patterns
- Experience deploying AI features into managed runtimes and cloud-native environments
- Familiarity with AWS, Azure, GCP, or private clouds
- Familiarity with Kubernetes internals, infrastructure automation, and CI/CD pipelines
- Experience with Jenkins, GitHub Actions, or Harness
- Strong understanding of distributed systems, telemetry, observability stacks, and hardware metrics
- Leadership experience connecting traditional software engineering with autonomous AI
- Excellent communication skills
- Ability to deliver scalable and reliable software in a high-velocity cross-functional environment
Responsibilities
- Design and build scalable multi-agent architectures for engineering and business workflows
- Integrate AI agents with internal services, SaaS platforms, and APIs
- Automate infrastructure actions including node cordoning, checkpointing, and hardware remediation
- Develop agents that generate code, refactor software, analyze telemetry, and correct system issues
- Architect short-term and long-term agent memory using protocols such as MCP
- Implement RAG pipelines grounded in telemetry and observability data
- Enforce agent evaluation, reliability, and security guardrails with LLM-as-a-Judge mechanisms
- Establish company-wide Harness engineering practices
- Automate the deployment, governance, and lifecycle management of agentic systems
- Apply CI/CD and feature flagging to agentic systems
- Collaborate with Kubernetes and infrastructure engineers to integrate agents into the platform control plane
