Full Stack Software Engineer

About Knovel: At our core, our passion is to craft novel AI and technology solutions that will shape tomorrow . We deploy cutting-edge technology that builds on cloud computing to proliferate AI, data and analytics solutions tailored to drive innovation and transform businesses. With our desire to push the boundaries of technology, we partner closely with our clients. Guidingt heir transformation with agility, we apply a structured technology transformation process attuned to their unique challenges. At Knovel Engineering, we blend technology with creativity to build unique solutions tailored for our customers. Job Title: Software Developer (Full Stack) Department: Engineering Reports To: Lead/Principal Engineer Location: Singapore Employment Type: Full-time, permanent Role Overview: We are looking for a Full Stack Software Engineer who can build reliable software systems and bring modern AI capabilities into production. You will work across our Python, JavaScript, and Golang stack to develop backend services, user-facing applications, APIs, databases, and AI-powered workflows. This role is ideal for someone who enjoys building practical products, moving quickly, and working at the intersection of software engineering and applied AI. You will help turn AI ideas into real systems that are scalable, observable, and reliable enough for production use. The role offers a competitive monthly base salary ranging from SGD 6,000 to 7,200complemented by annual performance-based bonuses that reward excellence and results. Responsibilities: Design, build, and maintain full stack applications using Python, JavaScript, Next.js, and Golang. Design and implement agentic AI workflows, including multi-step tasks, tool-using agents, memory, and multi-agent orchestration. Build and maintain AI Ops pipelines for LLM-powered systems, including deployment, monitoring, evaluation, prompt and version management, cost tracking, and observability. Integrate LLMs, AI models, APIs, data sources, and internal tools into production systems. Architect scalable systems covering service boundaries, data flow, caching, queues, retries, failure handling, and Performance. Design clean database schemas and write efficient, reliable queries. Define and implement well-documented API contracts for internal and external users. Containerize and deploy services using Docker and Kubernetes. Work closely with product, research, and engineering teams to bring AI features from prototype to production. Own the reliability, scalability, and performance of the systems you build, including monitoring, alerting, debugging, and incident response. Participate in code reviews, architecture discussions, technical planning, and product discovery. Move fast, ship thoughtfully, and continuously improve engineering quality. Collaborate with relevant stakeholders throughout the Software Development Life Cycle (SDLC). Contribute to technical documentation, runbooks and knowledge sharing to support long-term maintainability. Requirements: At least 2 – 6 years of experience building full stack applications, backend services, APIs, and production software systems. Strong professional experience in Python and JavaScript/Typescript. Working knowledge of Golang, or willingness to ramp up quickly. Experience with infrastructure-as-code tools such as Terraform and good-to-have experience with ansible. Experience with cloud and on-premise infrastructure. Experience with Docker and good-to-have experience with Kubernetes. Hands-on experience building or operating AI-powered systems, agentic workflows, or LLM-based applications. Familiarity with agent orchestration concepts such as multi-step reasoning flows, tool use, memory, multiple LLM calls, and multi-agent workflows. Practical understanding of AI Ops or MLOps concepts, including model or prompt versioning, evaluation pipelines, monitoring, observability, and production support. Solid understanding of system design principles, including scalability, reliability, caching, load balancing, and distributed systems trade-offs. Experience designing and consuming APIs such as REST, gRPC, or GraphQL, including authentication, versioning, and documentation. Experience with databases, schema design, query optimization, and data flow design. Strong debugging, problem-solving, communication, and ownership mindset. Comfortable working in a fast-moving startup environment with evolving priorities. Preferred skills and experiences: Experience wit…