Lead/Senior Lead Software Engineer - Agentic AI Engineering (Enterprise Asset Management)

We are looking for a talented Lead/Senior Software Engineer to join our Enterprise Asset Management team and play a leading role in designing, developing, and implementing cloud-based enterprise solutions. The ideal candidate will demonstrate a strong leadership mindset, solid operational experience, and excellent problem-solving and communication skills. In this role, you will evaluate, implement, and extend enterprise solutions while driving continuous improvements in software engineering practices across the team. You will be responsible for delivering scalable, reliable, and high-quality Enterprise Asset Management solutions by leveraging the right technologies, tools, processes, and engineering practices. As a technical leader, you will champion industry best practices to enhance engineering efficiency, solution quality, maintainability, and operational excellence. We are particularly looking for candidates who embrace modern AI-driven engineering practices, including agentic AI approaches, and effectively apply them throughout the entire software development lifecycle from solution design and development through testing, deployment, and customer acceptance to enable smarter engineering, accelerate delivery, and drive continuous innovation.

Business mindset

Demonstrates the ability to align engineering decisions with business goals, focusing on initiatives that deliver measurable value. Understands the commercial impact of technical choices, balances investment against business outcomes, and helps teams make decisions that support organizational success.

Builds for customers

Demonstrate a customer-focused mindset by making technical decisions based on customer needs and feedback. Works directly with customers to solve adoption, performance, and design challenges, and uses those insights to guide technical direction while promoting a culture that prioritizes customer outcomes.

Drives progress with accountability

Takes ownership of delivering results by removing blockers, making clear priorities, and maintaining high-quality standards. Delivers on commitments or raises risks early when plans need to change. Make proactive decisions on technical debt, investments, and quality, while setting clear expectations and standards for others to follow.

Thinks AI-native

Uses AI tools effectively to improve engineering productivity and quality, understanding when AI adds value and when traditional approaches are more appropriate. Promotes the adoption of AI as a core engineering capability and helps the team build stronger AI-assisted development practices.

• Strong hands-on experience with Go and modern backend development, ideally with TypeScript/Node.js.
• Experience designing and building microservices, event-driven systems, and RESTful APIs using technologies such as Kafka, Redpanda, and Kubernetes.
• Solid understanding of Domain-Driven Design (DDD), bounded contexts, service decomposition, and distributed system design.
• Experience with PostgreSQL, MongoDB, and cloud platforms such as AWS and Azure.
• Strong knowledge of CI/CD, automated testing (unit, integration, and end-to-end), observability, and production operations.
• Understanding secure software development, authentication/authorization, and DevSecOps practices.
• Experience using AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, or similar.
• Familiarity with AI-assisted Spec-Driven Development (SDD).
• Strong analytical and problem-solving skills, with the ability to lead technical initiatives and mentor engineers.

Beneficial

• Experience with React and modern frontend development.
• Experience building Enterprise SaaS or ERP products.
• Knowledge of LLMs, AI agents, RAG, context engineering, and AI evaluation in production environments.
• Experience designing and delivering enterprise-grade AI-powered applications.