Senior Software Engineer (AI)

Founded in 2014, Circles is a global technology company reimagining the telco industry with its innovative SaaS platform, empowering telco operators worldwide to effortlessly launch innovative digital brands or refresh existing ones, accelerating their transformation into techcos.

Today, Circles partners with leading telco operators across multiple countries and continents, including KDDI Corporation, Etisalat Group (e&), AT&T, and Telkomsel, creating blueprints for future telco and digital experiences enjoyed by millions of consumers globally.

Besides its SaaS business, Circles operates three other distinct businesses:

• Circles.Life: A wholly-owned digital lifestyle telco brand based in Singapore, Circles.Life is powered by Circles’ SaaS platform and pioneering go-to-market strategies. It is the digital market leader in Singapore and has won numerous awards for marketing, customer service, and innovative product offerings beyond connectivity.
• Circles Aspire: A global provider of Communications Platform-as-a-Service (CPaaS) solutions. Its cloud-based Experience Cloud platform enables enterprises, service providers and developers to deliver and scale mobile, messaging, IoT, and connectivity services worldwide.
• Jetpac: Specializing in travel tech solutions, Jetpac provides seamless eSIM roaming for over 200 destinations and innovative travel lifestyle products, redefining connectivity for digital travelers. Jetpac was awarded Travel eSIM of the Year.

Circles is backed by renowned global investors, including Peak XV Partners (formerly Sequoia), Warburg Pincus, Founders Fund, and EDBI (the investment arm of the Singapore Economic Development Board), with a track record of backing industry challengers.

About The Role We are looking for an AI Engineer to build and scale production-grade AI capabilities across our core backend services. You will design agentic workflows, integrate LLM-powered endpoints, and work on delivery lifecycle from prototype to production reliability.

Primary Scope

• Design, implement, and maintain AI/LLM features across backend services.
• Build secure, observable API integrations for AI use cases in consumer-facing journeys.
• Partner with product, design, and frontend teams to ship AI features with measurable business impact.

Key responsibilities of the AI Engineer shall include (but not be limited to):

• Collaborate with Product and Design teams to identify and build agentic AI use cases for consumer-facing journeys.
• Design and implement agentic workflows with planning and execution loops, safe tool/function calling, and strong failure handling.
• Build RAG pipelines, including document ingestion, chunking, embeddings, vector indexing, retrieval tuning, and grounded responses with citations where required.
• Develop secure and scalable AI APIs, SDKs, and integrations for frontend, internal systems, data sources, and third-party tools.
• Implement authentication, least-privilege access, RBAC, rate limits, retries, timeouts, budget controls, and provider failover strategies.
• Apply safety and compliance guardrails such as PII redaction or masking, content moderation, audit logging, and policy-aligned access controls.
• Define and automate evaluation frameworks to measure task success, response quality, hallucination, latency, and cost.
• Set up observability for AI systems using traces, metrics, logs, dashboards, and cost or latency monitoring.
• Optimize reliability, performance, and cost through caching, queuing, retries, timeouts, and model/provider fallback mechanisms.
• Contribute to CI/CD, infrastructure-as-code, automated testing, and production deployment processes.
• Drive production readiness through clear documentation, runbooks, staged rollout plans, and incident response support.
• Work closely with backend, frontend, and QA teams through sprint planning, technical design reviews, and code reviews.
• Write clean, well-tested, maintainable, and production-ready code.
• Resource Skills Requirement

The AI Engineer Shall Possess The Following Qualifications

• Proven experience designing, building, and operating agentic AI/LLM systems in production
• Strong proficiency in Python; familiarity with TypeScript/Node.js or Golang is a plus
• Hands-on with agent orchestration and tool/function calling; ability to design planning/execution loops and multi-agent workflows
• Strong RAG expertise, including document ingestion, chunki…