Uni Internship Jan to July 2027 - Multi-Agent AI Systems: Orchestrating Agentic Workflows

Join Synapxe as an intern and see how you can contribute in powering a healthier Singapore. Internship@Synapxe is where curiosity meets impact! You would be able to gain practical experience, hone your skills, and be part of meaningful work that improves health through technology. As an intern you will join the Data Science & AI team to explore agentic AI for healthcare applications. This internship focuses on developing and evaluating multi-agent workflows using modern AI frameworks and cloud platforms to support safe, reliable, and scalable healthcare solutions. Interns will gain hands-on experience in agent orchestration, workflow design, deployment, and observability in enterprise environments. The Selected Intern(s) Will Assist In Following Phase 1 – Orchestration Foundations and Landscape Survey orchestration topologies (e.g. supervisor, swarm, graph, and sequential) and agent communication standards such as MCP and A2A Prototype collaborative healthcare workflows using visual workflow builders such as n8n Explore agent roles, routing mechanisms, branching logic, and human oversight within multi-agent workflows Design role-specialised agent teams for healthcare use cases Phase 2 – Building the Production Orchestration Layer Rebuild and operationalise workflows using the Strands Agents SDK Deploy workflows on AWS Bedrock AgentCore Runtime and compare deployment approaches with self-managed hosting Implement agent state management, handoffs, result synthesis, subagent architectures, and context engineering techniques Integrate AgentCore Memory, Gateway, Identity, and MCP-based tool integrations Develop Agent Skills to support reusable domain-specific expertise Support observability, tracing, debugging, and performance monitoring across agent workflows Phase 3 – Hardening, Governance and Deployment Implement guardrails, cost controls, loop limits, and evaluation approaches for workflow quality and safety Apply human-in-command governance practices for healthcare-related workflows Evaluate and optimise workflows for cost, latency, throttling, concurrency, and task success rates Document architecture designs, orchestration workflows, and implementation approaches Prepare presentations and share project findings with the team About You Undergraduate currently in Year 2 or Year 3, pursuing a degree in Business Analytics, Business Artificial Intelligence Systems, Information Systems, Computer Science, Computer Engineering, Data Science, or a related discipline Strong proficiency in Python programming, with solid coding fundamentals Understanding of Generative AI concepts, including prompting, Retrieval-Augmented Generation (RAG), and working with LLM APIs Familiarity with agent frameworks and tools (e.g. LangChain, LlamaIndex, Strands Agents SDK, or similar open-source frameworks) Basic understanding of API integration, including connecting AI agents to external tools and data sources Familiarity with version control tools (e.g. Git) and collaborative development workflows Proficiency with development tools (e.g. VS Code, Jupyter notebooks) Exposure to cloud platforms (e.g. AWS, Azure, GCP) is a plus Exposure to advanced topics such as multi-agent systems, workflow orchestration, agent communication standards (e.g. MCP, A2A), or model evaluation is an advantage Independent, fast-learner, and self-driven Good team player with strong analytical and communication skills Ability to multitask and work effectively as part of a multidisciplinary team Passionate and keen to make a difference to re-imagine the future of HealthTech Want a glimpse into life at Synapxe? Follow us on TikTok, Instagram, and LinkedIn for exciting updates, stories, and behind‑the‑scenes content! TikTok | Instagram | LinkedIn