Sr. Software Engineer (Full Stack)

We are looking for a senior engineer who spans full-stack application development and/or SAP application engineering — building end-to-end features across front-end, back-end, and integration (or SAP modules / extensions), owning quality from UI to data. The role is hands-on and senior: leading feature design, integrating across systems, and mentoring engineers.

The defining shift for this seat in 2026 is fluency with AI-assisted development and building features that integrate LLMs, retrieval, and agents where they add value. The senior full-stack engineer is increasingly an orchestrator — combining traditional application code with AI capabilities and verifying AI-assisted output rather than shipping it blind.

The value this person brings is versatile, end-to-end delivery of high-quality features across the stack (or SAP landscape), increasingly AI-integrated with observability.

We are seeking a versatile engineer with end-to-end ownership who collaborates well across the stack or functions, is quality-focused, and mentors effectively. They deliver pragmatically and verify AI-assisted code.

This is a senior IC profile that partners across engineering, product, data, SAP functional teams, and QA. It suits someone open to a hybrid or remote-first engagement, and to mobilization to the Middle East, Europe, or North America depending on the client. The person we want owns features end to end.

A strong candidate for this role has delivered features end to end (or across SAP) and owned quality throughout — someone who has integrated across systems and mentored engineers. They bring an openness to integrating models / agents where valuable, with observability.

In practice, the responsibilities break down as follows:

• Full-stack / SAP engineering: Build end-to-end features across front-end, back-end, and integration; or develop / extend SAP modules and integrations; own quality from UI to data (or across the SAP landscape).
• Integration: Integrate across systems and services reliably.
• Quality & mentorship: Drive testing and code review; verify AI-assisted code; mentor engineers.
• AI integration: Integrate LLMs, retrieval, and agents (Amazon Bedrock or equivalent) into features where valuable, with observability and evaluation.

We want to see an engineer with genuine end-to-end breadth (or SAP depth) who keeps quality high and integrations reliable, and who is comfortable adding AI where it helps and verifying it.

Core engineering

• Full-stack: front-end framework + back-end language + databases + APIs; OR SAP (ABAP, Fiori / UI5, integration, S/4HANA).
• Testing, CI/CD, cloud (AWS, Azure, GCP or equivalent).

Engineering performance (KPIs from research)

• Steers feature-delivery quality, defect / escape rate, integration reliability, and test coverage — plus verification quality on AI-assisted code.

Modern Agentic AI / AIOps (niche areas we are seeking — depth explored at interview)

• Features that use autonomous agents, retrieval, and tool use.
• Integrating models / agents (Amazon Bedrock or equivalent) into features.
• Observability and evaluation for AI-integrated features.

These niche AI areas are seeds we are looking for; depth will be explored during the interview process.

This role is delivered through Solutions Chapter Group's Human Resources chapter (Chapter 12) as a Recruitment Process Outsourcing (RPO) engagement, under our Technical Recruitment stream. Rather than a "post-and-pray" marketplace approach, we use a Curated Professional Recruitment model: candidate profiles are pre-vetted in our internal database, and when a required profile isn't already available, our dedicated Scout network conducts global headhunting to secure it. We screen and match candidates against each client's specific requirements, and placements may be remote or an on-site deployment with mobilization to the Middle East, Europe, or the United States.

From a recruitment-fit perspective, we screen for:

• Versatile, end-to-end ownership.
• Strong collaboration across the stack / functions.
• Quality focus and effective mentorship.
• Pragmatic delivery and verification of AI-assisted code.
• Openness to the engagement model (remote or mobilized on-site) and readiness for cross-region deployment.

Areas to explore at interview *(topics only)*

• An end-to-end feature you built
• A tricky integration