Principal Software Development Engineer - Platform Development (AWS/Azure)

Job Requisition ID #

25WD88166

Position Overview:

As a Principal Software Development Engineer, you will join the Engineering & DevOps Services (EDS) team within AI, Data & Automation (AIDA). Our team drives the Enterprise AI Strategy by building and operationalising the Enterprise AI Fabric, enabling intelligent search, LLM-powered workflows, and AI-driven agents. Our team has a lot of visibility and the impact of our work is directly related to business results. We value the culture, transparency and collaboration in our team and in general, we take pride in our global diversity and how we work and talk with one another. This is a hybrid role.

Job Description:

We are looking for a highly skilled Principal Software Development Engineer (SDE-IV) to lead the development and operationalisation of AI Platforms. This role combines hands-on engineering with platform ownership, ensuring the successful implementation of tools and frameworks that enable intelligent search, LLM-powered actions, and AI-driven productivity agents across the organisation.

You will play a pivotal role in designing, building, and deploying AI-enabled solutions that integrate with enterprise collaboration platforms and intranet websites. As a senior engineer, you will also guide junior developers, influence architectural decisions, and ensure scalability, security, and adoption of enterprise AI tools.

Responsibilities

Technical Excellence & Engineering

• Demonstrate deep expertise in areas such as cloud infrastructure, distributed systems, and event-driven architectures
• Design and evolve large-scale, reliable, and secure systems with a focus on performance, maintainability, and operational excellence
• Stay hands-on when needed—prototyping, debugging, and delivering high-impact components
• Apply deep platform development expertise in AWS Cloud, including caching, load balancing, auto-scaling, database redundancy and resiliency, performance monitoring, hosting patterns, and full-stack platform architecture across all layers

Platform Engineering & Architecture

• Build foundational platforms and shared services that enable rapid development and innovation across multiple teams
• Design systems for extensibility, multi-tenancy, and future growth — not just immediate product requirements
• Champion reusable “building blocks” over siloed point solutions
• Drive adoption of AI Agent Platforms, working with emerging standards like MCP, embedding Trusted AI governance, and enabling LLM-powered actions across enterprise systems

Strategic & Business Alignment

• Connect technical decisions to broader business goals (e.g., cost optimization, customer impact, faster time to market)
• Prioritize initiatives based on a balance of technical merit and strategic business value
• Influence product direction through a strong technical voice in cross-functional forums

Technical Leadership

• Lead through influence and expertise across diverse engineering teams
• Drive architectural decisions, mentor senior engineers, and contribute to a culture of engineering rigor and excellence
• Facilitate knowledge sharing, tech strategy reviews, and cross-team collaboration

Systems Thinking & Complex Problem Solving

• Approach challenges holistically, considering code, infrastructure, team dynamics, and business context
• Navigate ambiguity and deliver clarity through well-thought-out decisions and forward-looking designs
• Balance short-term execution with long-term system health and scalability

Cross-Functional Communication & Collaboration

• Communicate clearly and effectively with technical and non-technical audiences, from engineers to executives
• Adapt communication styles to suit the audience — technical deep dives vs. strategic roadmaps
• Build strong partnerships with Product, Infrastructure, Security, and Business teams

Execution & Results Delivery

• Own delivery from concept through deployment and adoption — ensuring business and customer impact
• Decompose complex initiatives into actionable work across teams, ensuring high-quality execution
• Lead cross-team engineering programs with clarity, accountability, and alignment

Adaptability & Continuous Learning

• Stay current on evolving technologies, best practices, and industry trends
• Encourage experimentation and innovation in tools, architecture, and engineering processes
• Foster a team culture grounded in curiosity, learning, and continuous improvement

Minimum Qualifications

• 10+ years of professional software development experience, including deep expertise in building and scaling distributed systems, cloud-native platforms (AWS, Azure, or GCP), and event-driven architectures
• Proven platform development experience in AWS Cloud across caching, load balancing, auto-scaling, database redundancy/resiliency, performance monitoring, hosting patterns, and full-stack platform architecture
• Expertise in Python (or similar modern programming languages) with experience delivering scalable, production-grade systems
• Demonstrated ownership of end-to-end system design, development, and operational excellence for critical production systems
• Strong understanding of security best practices, observability (monitoring, logging, alerting), and reliability engineering principles
• Experience in designing and evolving AI/LLM-driven platforms, including AI Agent Platforms, MCP, Trusted AI governance, and LLM-enabled enterprise actions
• Proven ability to design and evolve foundational platforms that accelerate development across multiple business units
• Demonstrated ownership of initiatives from idea to production launch, with measurable business or customer impact
• Experience working across multiple technical domains (e.g., backend, cloud infrastructure, security, data engineering, automation, CI/CD) and demonstrated ability to quickly ramp up on new technologies
• Experience leading cross-functional initiatives and collaborating with product, security, operations, infrastructure, and business teams
• Ability to solve ambiguous, complex problems by considering technical, business, and organizational perspectives
• Excellent communication and influencing skills with the ability to engage diverse technical and non-technical stakeholders, including senior leadership
• Experience mentoring senior engineers and fostering a culture of engineering excellence
• Bachelor’s degree in Computer Science, Engineering, or related technical field (or equivalent practical experience)

Preferred Qualifications

• Experience in participating or driving "Tech Culture" initiatives like Engineering Excellence and Reliability Programs
• Master’s degree in Computer Science or a related technical discipline
• Experience in building AI and Machine Learning solutions, with practical exposure to AI Agent Platforms, Trusted AI, and LLM-enabled automation
• Experience scaling systems to users or high-throughput enterprise environments
• Contributions to open-source projects, technical publications, or speaking at major industry events
• Hands-on experience with modern DevOps practices, CI/CD pipelines, and infrastructure as code (IaC)