Desing and build central AI platform development and governance: AWS Bedrock fronted by an LLM gateway (LiteLLM, Portkey, or similar). Token budgets, rate limits, key management, guardrails, audit logging, observability, cost controls.
Engineer the technical architecture of 1GLOBAL's internal AI tools and MCP servers, including RAG pipelines, vector search, LLM integration, and conversational interfaces.
Build secure ingestion and indexing pipelines for internal knowledge sources (Confluence, SharePoint, document repositories, internal APIs) with appropriate access controls.
Develop backend services and APIs that expose AI capabilities to internal users and, over time, to product teams building customer-facing features.
Establish engineering standards for the AI function: testing, deployment, monitoring, and model evaluation frameworks.
Own the full development lifecycle from requirements through production monitoring, with a bias toward shipping and iterating.
Requirements
About You
4+ years of software engineering experience, with meaningful recent work integrating LLMs into real systems. Deep traditional ML or model-training background is not required.
Strong generalist backend engineer. Python proficiency is expected. You're comfortable building a full-stack internal tool end-to-end and shipping it without waiting for permission.
Hands-on experience with AI gateways or model routing layers such as LiteLLM, Portkey, or AWS Bedrock — including token limits, guardrails, observability, and cost management.
Practical experience building MCP servers, or strong fluency with similar tool-calling and agent integration patterns. MCP specifically is a plus.
Power user of AI coding agents (Claude Code, Codex, or similar). You can define skills, workflows, and standards that make other engineers more effective — not just use the tools yourself.
Working knowledge of RAG, vector search, and LLM evaluation. You understand the trade-offs and can build a solid pipeline. Depth in this area is a plus, not a prerequisite.
Comfortable with CI/CD, containerization (Docker, Kubernetes), and infrastructure-as-code.
Familiarity with data security practices - PII handling, access controls, data classification. Experience in regulated environments (telecommunications, financial services, ISO 27001) is an advantage.
Strong communicator. Much of this role is making other engineers and non-technical teams more effective. You can explain technical trade-offs clearly. Fluent in English.
Self-directed and comfortable with ambiguity. You will be shaping a function, not joining a mature one.
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