Fullstack Software Engineer – GenAI & Agentic Solutions

CMC-APAC PRIVATE LIMITED; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

CMC-APAC PRIVATE LIMITED seeks a hands-on Software Engineer to collaborate closely with business stakeholders and leverage an enterprise Generative AI platform to deliver AI-driven automation capabilities.

The role involves working directly with users, translating challenges into use cases, building applications and agentic workflows, and driving adoption from concept to production.

Qualifications

• Minimum 5 years of software engineering experience with ownership of production applications from requirements definition through deployment and operational support.
• Strong backend API development, integration patterns, asynchronous processing, testing, debugging, and solution architecture.
• Experience with relational databases, particularly PostgreSQL, data modeling, query optimization, data pipelines, enterprise search, and vector retrieval services.

Responsibilities

• Understand processes, challenges, data constraints, and target outcomes with business teams.
• Conduct discovery workshops and gather requirements to define use cases and measurable success metrics.
• Develop prototypes quickly for user validation and refine solutions based on feedback.
• Design, develop, and maintain AI agents and workflow orchestration solutions using LangGraph, LangChain, or equivalent frameworks.
• Build backend services, APIs, integrations, authentication components, workflow engines, and user interfaces where needed.
• Ensure data governance, quality, lineage, and access control across data pipelines and applications.
• Define testing approaches, evaluation datasets, and monitor solution reliability, latency, and operational cost.

Skills

Python

API development

Asynchronous processing

PostgreSQL

LangChain

LangGraph

n8n

LLM-powered apps

Tools

LangGraph

LangChain

LlamaIndex

n8n

Job description

Position Overview

Seeking a hands-on Software Engineer to collaborate closely with business stakeholders and leverage an enterprise Generative AI platform to deliver impactful AI-driven and automation capabilities. The role involves working directly with users, understanding operational challenges, shaping solutions, building applications and agentic workflows, and driving adoption from concept to production.

Primary Duties

Business Engagement & Requirements Definition

• Work alongside business teams to understand existing processes, operational challenges, data considerations, constraints, and target outcomes.
• Conduct discovery workshops and requirement-gathering sessions.
• Convert business needs into use cases, user stories, solution blueprints, and measurable success metrics.
• Challenge assumptions and help stakeholders prioritize opportunities.

Prototype Development & Delivery

• Quickly develop proof-of-concepts and prototypes for user validation.
• Gather feedback and continuously refine solutions.
• Transition validated concepts into production-grade implementations while maintaining engineering quality.

Agent & Workflow Development

• Design, develop, and maintain AI agents and workflow orchestration solutions.
• Utilize technologies such as LangGraph, LangChain, n8n, or equivalent frameworks.
• Implement reasoning flows, tool integrations, state management, approval processes, exception handling, and workflow controls.

Application Engineering

• Develop custom software applications tailored to business requirements.
• Build backend services, APIs, integrations, authentication components, workflow engines, and user-facing interfaces where required.

Data Integration & Knowledge Services

• Build data ingestion, transformation, retrieval, and processing pipelines.
• Integrate enterprise applications, databases, document repositories, APIs, search platforms, and vector-based retrieval services.
• Ensure proper governance around data quality, lineage, and access control.

Backend Development & Database Management

• Develop scalable and secure backend systems and APIs.
• Design and optimize relational database structures using technologies such as Python, FastAPI, and PostgreSQL.
• Troubleshoot integration, performance, state-management, and operational issues.

AI Evaluation & Monitoring

• Define testing approaches, acceptance criteria, and evaluation datasets.
• Measure solution effectiveness, reliability, latency, operational cost, and tool execution success.
• Implement monitoring, tracing, and observability capabilities.
• Improve prompts, retrieval methods, workflows, and safety mechanisms through continuous iteration.

Security & Responsible AI

• Apply secure development practices and data protection controls.
• Implement least-privilege access, auditability, human oversight, prompt-injection protection, and output governance measures.
• Align solutions to organizational security and risk requirements.

Production Rollout & Knowledge Transfer

• Lead production readiness activities, deployment, testing, documentation, and support.
• Enable users through training and adoption activities.
• Monitor business outcomes and identify opportunities to enhance reusable platform capabilities.

Required Qualifications

Professional Experience

• Minimum 5 years of software engineering experience with ownership of production applications from requirements definition through deployment and operational support.

Backend Engineering

• Strong expertise in Python or a modern backend programming language.
• Experience in API development, integration patterns, asynchronous processing, testing, debugging, and solution architecture.

Data & Database Skills

• Strong experience working with relational databases, particularly PostgreSQL.
• Knowledge of data modeling, query optimization, data pipelines, enterprise search, and vector retrieval services.

Generative AI Experience

• Experience building LLM-powered applications, RAG platforms, tool-calling agents, agentic workflows, or automation solutions.
• Familiarity with LangGraph, LangChain, LlamaIndex, n8n, or equivalent technologies.

Cloud Technologies

• Experience deploying and operating cloud-native solutions.
• Knowledge of AWS services such as Bedrock and OpenSearch is advantageous.
• Equivalent experience in Azure or Google Cloud environments is acceptable.

Stakeholder Management

• Ability to communicate effectively with technical and non-technical audiences.
• Experience facilitating discussions, gathering requirements, managing expectations, and supporting adoption.

Working Style

• Comfortable operating in ambiguous environments.
• Able to quickly learn unfamiliar business domains.
• Capable of balancing speed of delivery, user value, security, reliability, and maintainability.

Preferred Experience

• Consulting, solutions engineering, internal product delivery, or forward-deployed engineering experience.
• Experience with workflow automation platforms such as n8n or Flowise.
• Exposure to LLM evaluation, observability, red-teaming, tracing, or AI quality assurance methodologies.
• Experience supporting applications in highly regulated environments with stringent privacy, cybersecurity, accessibility, or public-sector compliance requirements.