Senior AI Engineer (Agents & Applications)
Firmus Technologies3 hours ago
Singapore, SingaporeSenior
Responsibilities
- Design, build, and operate agentic applications for AI-factory planning, commissioning, validation, workload onboarding, benchmarking, scheduling, operations, maintenance, incident response, and continuous improvement.
- Define and implement single-agent, multi-agent, workflow-based, event-driven, and human-in-the-loop architectures.
- Build orchestration workflows, specialist domain agents, RAG pipelines, knowledge-ingestion systems, context pipelines, memory systems, and governed tool and API integrations.
- Implement model routing, fallback strategies, durable execution, retries, recovery, escalation, approval controls, policy enforcement, and audit logging.
- Develop offline replay, simulation, shadow-mode, what-if evaluation, agent observability, regression testing, and operational-outcome measurement capabilities.
- Partner with inference, Kubernetes, scheduler, platform, security, UX, product, and operations teams to deliver production workflows and measurable outcomes.
Requirements
- At least 5 years of software engineering experience, including at least 3 years building AI/ML applications, distributed systems, automation platforms, data products, or production workflow systems.
- Demonstrated experience delivering LLM-powered, agentic, retrieval-augmented, decision-support, or operational-automation applications into production.
- Strong Python expertise with FastAPI or comparable API frameworks, asynchronous programming, event-driven services, distributed task execution, data pipelines, and API integrations.
- Hands-on experience with agent frameworks and the ability to build custom orchestration using state machines, graph execution, durable workflows, task queues, routers, planners, evaluators, and approval flows.
- Experience with workflow and orchestration technologies, RAG architectures, vector/search/graph databases, self-hosted or managed LLM inference, model routing, embeddings, reranking, tool calling, and structured outputs.
- Understanding of REST, gRPC, WebSockets, event streams, OpenAPI, JSON Schema, Model Context Protocol, cloud-native AI platforms, Kubernetes, containers, scheduling, model serving, GPU resources, observability, and multi-tenancy.
- Understanding of agent security and responsible-AI controls including prompt injection defenses, tenant isolation, authorization, workload identity, auditability, output validation, sandboxing, and human-in-the-loop safeguards.
- Experience with agent evaluation and observability tools or equivalent custom tooling.
Benefits
- Permanent full-time employment based in Singapore.
- Founder-led environment with accessible leadership, fast decision-making, early ownership, and opportunities to grow into new domains.
- Work alongside experts in AI infrastructure, energy systems, and next-generation compute on sustainable AI-factory technology.
Tech Stack
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