Our client is a fast-growing AI company building enterprise-grade agentic automation solutions for large organizations. They are looking for a hands-on, customer-facing engineer to work directly with enterprise clients and bring AI-driven automation workflows into production.

This role is best suited for a strong backend engineer who enjoys solving ambiguous customer problems, working close to real business operations, and moving from discovery to implementation quickly. You will help clients identify where AI agents can create practical impact, then design, build, integrate, deploy, and iterate solutions within complex enterprise environments.

You will work across backend engineering, solution design, integrations, data flows, deployment, and customer engagement, with a strong focus on reliability, business value, and production outcomes.

Key Responsibilities

• Partner directly with enterprise customers to understand their workflows, pain points, technical environments, and success criteria.
• Translate ambiguous business problems into clear technical plans, solution designs, and production-ready implementations.
• Build, configure, and deploy AI agents and automation workflows that connect with customer systems, data sources, APIs, and business processes.
• Own the delivery lifecycle from discovery and scoping through build, testing, launch, monitoring, and ongoing iteration.
• Write high-quality code for backend logic, integrations, workflow automation, data handling, and deployment requirements.
• Work with real customer data and production environments to test performance, measure outcomes, and improve solution effectiveness.
• Collaborate with product and engineering teams to improve the platform based on customer needs, deployment learnings, and field feedback.
• Run technical workshops, guide customers through implementation decisions, and explain technical trade-offs clearly to both technical and non-technical stakeholders.
• Identify repeatable patterns, create documentation, improve internal tools, and help scale delivery practices as the team grows.
• Take ownership of reliability, performance, maintainability, and long-term customer success after deployment.

Requirements

• Minimum 4–7 years of experience in software engineering, backend engineering, solutions engineering, implementation engineering, technical consulting, or similar hands-on technical roles.
• Strong backend engineering fundamentals, including system design, APIs, integrations, data flows, and production systems.
• Experience building or deploying solutions in complex customer environments, especially where requirements are ambiguous or evolving.
• Comfort working directly with enterprise customers, including business, operations, IT, and technical stakeholders.
• Ability to quickly understand customer workflows and identify where automation or AI can deliver practical business impact.
• Strong ownership mindset, with the ability to create clarity, drive decisions, and move projects forward independently.
• Clear communication skills, with the ability to explain technical concepts, implementation plans, risks, and trade-offs in a practical way.
• Experience working with production systems, including testing, debugging, monitoring, performance improvement, and ongoing iteration.
• Genuine curiosity about AI agents, automation, LLM-powered systems, and how AI can be applied to real operational problems.
• Regular use of AI tools and a practical understanding of what current AI technologies can and cannot do.
• Comfort operating in a fast-moving, early-stage environment where priorities may shift and solutions need to be developed quickly but thoughtfully.

Good to Have

• Experience in enterprise implementation, deployment, professional services, customer engineering, or technical consulting.
• Exposure to AI agents, LLM applications, automation platforms, workflow tools, or data-heavy enterprise systems.
• Experience working with large enterprise clients in Singapore, especially across FSI, telco, insurance, aviation, or other complex industries.
• Startup or zero-to-one environment experience.