Full Stack Engineer (GenAI and Agentic Applications)

CAPGEMINI SINGAPORE PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Capgemini Singapore is seeking an experienced Software Engineer to work with business units on our enterprise GenAI platform. You will translate ambiguous needs into scoped solutions and own delivery from discovery to production rollout, adoption and handover.

You'll build agentic workflows and custom apps using LangGraph, LangChain and n8n, with strong backend, API, database, evaluation and security engineering across platforms.

Qualifications

• 5+ years of software engineering, with production ownership.
• Backend: Python or modern language, API design, async processing.
• Relational databases, preferably PostgreSQL, data modelling and queries.
• GenAI and agentic systems: building LLM-enabled apps, tool-calling.
• Cloud deployment experience; AWS Bedrock/OpenSearch preferred.

Responsibilities

• Embed with business units to understand workflows, pain points, data, constraints and outcomes; translate needs into prioritised use cases and solution designs.
• Prototype rapidly, validate with users, and push viable solutions to production.
• Design and implement AI workflows and agent-based systems using Python-based frameworks and orchestration tools.
• Build backend services, APIs, integrations, authentication, workflow logic and lightweight UIs where needed.
• Design robust data ingestion, transformation, and retrieval pipelines; integrate enterprise systems and search/vector services.
• Develop secure, scalable backend services and data models; diagnose integration and performance issues.
• Define evaluation datasets, monitor quality, latency and cost; implement observability and safeguards.
• Apply secure engineering practices and governance for responsible AI and compliance.

Skills

Python

API design

Asynchronous processing

System architecture

PostgreSQL

Data pipelines

LangGraph

LangChain

n8n

Cloud deployment

OpenSearch

Tools

LangGraph

LangChain

LlamaIndex

n8n

PostgreSQL

FastAPI

Python

AWS Bedrock

OpenSearch

Job description

About Capgemini

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion.

About the Role

We are looking for an experienced, product-minded Software Engineer to work directly with business units and use our established enterprise GenAI platform to deliver high-impact AI and automation solutions. In this forward-deployed role, you will partner closely with business users to understand their workflows, translate often ambiguous needs into well-scoped solutions, and own delivery from discovery and rapid prototyping through production rollout, adoption, and handover. You will build agentic workflows and custom applications using frameworks such as LangGraph and n8n, supported by strong backend, API, database, evaluation, and security engineering.

Responsibilities

• Business Discovery & Solution Shaping: Embed with business units to understand operational workflows, pain points, data, constraints, and intended outcomes. Facilitate discovery sessions, challenge assumptions, and translate needs into prioritised use cases, user stories, solution designs, and measurable success criteria.
• Rapid Prototyping & Iterative Delivery: Build working prototypes quickly, validate them with users, and iterate based on evidence. Balance speed with maintainable engineering and take viable solutions through production deployment.
• Agentic Workflow Engineering: Design and implement reliable AI workflows and agents using Python-based frameworks and orchestration tools such as LangGraph, LangChain, n8n, or equivalent technologies. Combine deterministic steps, LLM reasoning, tool calling, state management, human approvals, and exception handling as appropriate.
• Custom Application Development: Build fit-for-purpose applications around business use cases, including backend services, APIs, integrations, authentication, workflow logic, and lightweight user interfaces where needed.
• Data & Knowledge Integration: Design robust data ingestion, transformation, and retrieval pipelines. Integrate enterprise systems, databases, document repositories, APIs, and search or vector services while maintaining data quality, lineage, and access controls.
• Backend & Database Engineering: Develop secure, scalable backend services and APIs, and design relational data models using technologies such as Python, FastAPI, and PostgreSQL. Diagnose complex integration, performance, and state-management issues.
• AI Quality, Evaluation & Observability: Define evaluation datasets and acceptance criteria; test solution quality, reliability, latency, cost, and tool-call success; implement tracing and monitoring; and continuously improve prompts, retrieval, workflows, and safeguards.
• Security, Governance & Responsible AI: Apply secure engineering practices, least-privilege access, data protection, prompt-injection defences, output controls, auditability, and human oversight in line with government policies and the risk profile of each use case.
• Deployment, Adoption & Handover: Own production readiness, testing, rollout, documentation, user enablement, support, and knowledge transfer. Track adoption and business outcomes and incorporate field learnings into reusable patterns and improvements to the core platform.

Requirements

• Experience: 5+ years of software engineering experience, including demonstrated ownership of production applications from ambiguous requirements through deployment and support.
• Backend Engineering: Strong proficiency in Python or another modern backend language, API design, asynchronous processing, integration patterns, testing, debugging, and system architecture.
• Database & Data Engineering: Strong experience with relational databases, preferably PostgreSQL, including data modelling and query optimisation; practical knowledge of data pipelines, search, and vector retrieval is also required.
• GenAI & Agentic Systems: Hands-on experience building LLM-enabled applications, RAG solutions, tool-calling agents, or automated workflows using frameworks such as LangGraph, LangChain, LlamaIndex, n8n, or equivalent.
• Cloud & Production Delivery: Practical experience deploying and operating cloud-native applications. Familiarity with AWS and services such as Bedrock and OpenSearch is preferred, although equivalent Azure or GCP experience is acceptable.
• Stakeholder Partnership: Strong communication and facilitation skills, with the ability to work directly with non-technical users, clarify busin