Software Engineer (Back-End) - A26432

Activate Interactive Pte Ltd (“Activate”) is a leading technology consultancy headquartered in Singapore with a presence in Malaysia and Indonesia. Our clients are empowered with quality, cost-effective, and impactful end-to-end application development, like mobile and web applications, and cloud technology that remove technology roadblocks and increase their business efficiency.

We believe in positively impacting the lives of people around us and the environment we live in through the use of technology. Hence, we are committed to providing a conducive environment for all employees to realise their full potential, who in turn have the opportunity to continuously drive innovation.

We are searching for our next team members to join our growing team.

If you love the idea of being part of a growing company with exciting prospects in mobile and web technologies that create positive impact on people’s lives, then we would love to hear from you.

Co-Development Business Unit is hiring

You will work in Singapore Government Agencies

This is a fixed term contract role. The engagement is 1 year.

Internal Code: A26432

What will you do?

• Build, manage and monitor the centralised AI Foundation Platform (currently on Amazon Bedrock), providing secure access to foundation models for multi-modal data extraction, understanding and generation
• Maintain the AI infrastructure, including model access, provisioning, quotas, API integrations and service configurations across use cases
• Design and develop full-stack platform services, including backend APIs, middleware and admin or self-service portals, that let application teams consume AI capabilities consistently
• Integrate the AI platform with enterprise data sources and applications so AI outputs are context-aware, including Retrieval-Augmented Generation (RAG) pipelines, knowledge bases and vector stores
• Support model customisation (e.g. fine-tuning, prompt management, knowledge bases) and contribute to building the MinLaw domain ontology that guides AI applications
• Optimise platform performance, latency, throughput and cost, and ensure the scalability, availability and reliability of AI services
• Monitor and report Amazon Bedrock consumption and cost against budget, and recommend optimisation measures (e.g. model selection, prompt caching, provisioned throughput)
• Design and implement secure AI infrastructure aligned with the Agency's Enterprise Architecture and Government ICT security policies, including IAM, network isolation, encryption and secrets management
• Develop Infrastructure-as-Code and CI/CD pipelines to automate provisioning, deployment and release of AI platform components
• Build shared, reusable platform components so common AI capabilities are built once and used many times across divisions
• Deploy and manage monitoring tools for AI service performance, utilisation and health
• Troubleshoot and resolve platform issues across infrastructure and application layers, and take part in on-call escalations
• Work with DevSecOps Engineers, Solution Architect and application division system teams to deliver end-to-end solutions
• Review source code and solutions as part of the software development lifecycle process
• Produce and maintain technical documentation, runbooks and onboarding guides for application teams
• Prepare architecture and security submissions for the Architecture Review Board (ARB) and security reviews of AI platform changes
• Set up and operate the agentic AI infrastructure, including the agent runtime (e.g. Amazon Bedrock Agents / AgentCore), tool and API gateway, agent memory and state, and environments for development, testing and production
• Build and maintain the shared agentic AI modules (reusable agents, tools, connectors and orchestration patterns, including multi-agent workflows) that CAMP case management applications consume
• Provide each agent with its own identity and least-privilege access to tools and data, with network isolation, sandboxed tool execution, secrets management and a registry of approved agents and tools
• Set usage limits for agents (token, rate, step and spend quotas, timeouts) and an emergency stop (kill switch), working with the AI MLOps Engineer on guardrail enforcement
• Instrument agents and platform services with tracing, metrics and logs (e.g. OpenTelemetry, CloudWatch) covering model calls, tool calls and agent decisions, and define SLIs/SLOs and alerts for agentic AI services
• Onboard additional case management workflows and divisions to the agentic AI platform, with onboarding guides, reference implementations and capacity planning
• Provide technical inputs for the System Security Plan (SSP) and ICT&SS / IM8 compliance for agentic AI infrastructure.