Senior Software Engineer – AI & Agent Architecture (Retail & ECommerce)

About the role

We are looking for a Senior Software Engineer to design, develop and scale AI‑powered solutions for high‑availability production environments within our Retail & E‑Commerce practice. You will architect intelligent agents, autonomous workflows and AI‑native services that drive commerce initiatives.

Key responsibilities

• Design, develop and scale AI‑powered solutions for high‑availability production environments.
• Architect and implement intelligent agents, autonomous workflows and AI‑native services.
• Contribute across the full Software Development Life Cycle (SDLC), from technical design to deployment and optimization.
• Drive engineering best practices around software quality, observability, security, scalability and performance.
• Collaborate closely with Product, Engineering, Data and AI teams to accelerate AI‑driven commerce initiatives.
• Contribute to architectural decisions and help shape the long‑term evolution of the technology platform.
• Support technical excellence through code reviews, mentoring and knowledge sharing.

Required profile

• Bachelor's degree in Computer Science, Software Engineering, or a related field.
• Proven experience as a Senior Software Engineer in complex and scalable environments.
• Strong background in distributed systems architecture and modern software engineering principles.
• Experience designing and integrating AI‑driven applications, intelligent agents or automation workflows.
• Hands‑on experience with cloud‑native environments and production‑grade applications.
• Solid understanding of SDLC, CI/CD pipelines, automated testing and DevOps best practices.
• Experience working with LLMs, AI integrations and modern AI engineering ecosystems.
• Strong problem‑solving skills and ability to balance technical quality with business impact.
• Excellent communication and collaboration skills.

Required skills

• Distributed systems architecture
• Cloud‑native environments
• CI/CD pipelines
• Automated testing
• DevOps best practices
• Large Language Model (LLM) integration
• AI integrations