We are looking for a Senior AI Systems Engineer with a deep mastery of Golang to architect and build the next generation of our back-office automation platform. You will be the bridge between sophisticated AI models and production-grade software. This role is not just about prompt tuning; it is about building the high-performance engines, concurrency patterns, and system integrations that allow AI Agents to operate reliably at scale.
- Core Engine Development: Design and develop high-performance AI Agent engines in Golang, focusing on concurrency, low-latency execution, and scalable system architecture.
- AI Orchestration: Build robust prompt-chaining strategies and agentic workflows that integrate LLMs into our SaaS application.
- System Reliability: Monitor agent behavior and system-level metrics in Go to identify and mitigate hallucinations or performance degradation.
- Cross-Functional Leadership: Take technical ownership of AI initiatives, leading collaboration across BE/FE/SRE teams to drive system-level decisions.
- Optimization: Bridge the gap between Python-based AI research and Go-based production environments, ensuring seamless model serving and data flow.
Requirements
Technical
Must have
- 3 to 5 years of professional experience with Golang; a deep, idiomatic understanding of Goroutines, channels, and designing scalable, high-performance backend services.
- 2+ years of experience with Python.
- 5+ years of Web application development.
- Practical experience designing and optimizing prompts for LLMs in production environments.
Good understanding of:
- Backend development (e.g., web frameworks, databases).
- Cloud infrastructure (e.g., Azure, AWS, Terraform, serverless architecture).
- MLOps pipeline.
Experience in:
- Architectural design for multi-agent orchestration.
- LLM orchestration frameworks like AutoGen, LangChain, and LlamaIndex.
- RAG architecture and vector stores.
- Integrating AI services from platforms like Azure AI Foundry, AWS Bedrock, or GCP Vertex AI.
Nice to Have
- Basic understanding of frontend development (e.g., TypeScript/React).
- Understanding of AI system deployment from a security/compliance standpoint.
- Exposure to IaC and CI/CD in production systems.
- Experience in B2B application development.
- Experience in introducing traditional machine learning techniques and related ML pipelines to improve businesses.
Communication
- Strong English communication, both verbal and written.
- Experience in leading a project as a team leader.
- Experience in educating team members.
- Strong sense of ownership.
