Senior IT Tech Lead

Allied Reliability is seeking a Sr Tech Lead Software Engineering & AIto join a vibrant team within the Trading & Supply Capability Center (CC) in the IT Digital Engineering VPship. This role is accountable for leading the design development deployment and ongoing operation of production-grade digital products that combine strong software engineering foundations with applied AI and GenAI capabilities. The role carries a balanced 50:50 focus: driving modern software engineering practices across architecture APIs platforms cloud-native delivery reliability and security while also shaping the practical use of machine learning GenAI RAG and intelligent automation to solve business problems across multiple lines of business. The successful candidate will be responsible for delivering scalable maintainable and governed solutions that meet Shell quality standards and can be operated confidently in production.

All candidates must be local to Houston TX. This is a contract opportunity and does not offer sponsorship now or in the future.

Key Responsibilities

Design build and deploy production-grade applications and services that embed AI and GenAI capabilities in a secure scalable and maintainable way.

Build and evolve core engineering foundations including APIs reusable services cloud-native deployment patterns CI/CD pipelines monitoring and operational support for AI-enabled products.

Work closely with platform infrastructure data engineering and DevSecOps teams to improve deployment velocity runtime resilience security controls and engineering efficiency.

Lead the technical direction of software engineering and AI initiatives ensuring a balanced focus on product architecture engineering quality and applied AI delivery.

Mentor software engineers and AI engineers raising the bar on coding standards system design testing delivery practices and responsible use of AI technologies.

Define engineering and evaluation practices that ensure software quality model quality reliability performance observability and compliance for AI tooling and services.

Guide the strategic adoption of AI and GenAI by identifying high-value opportunities and turning them into robust engineering outcomes that can scale across the enterprise.

Partner with Product Management and business stakeholders to translate requirements into well-architected software solutions AI-enabled workflows and delivery roadmaps.

Stay current with emerging software engineering and AI practices continuously improving delivery approaches technical standards and relationships across Shell industry and academia.

Contribute to technical communities of practice and centres of excellence helping to strengthen engineering capability reusable patterns and responsible AI adoption.

Professional Qualifications & Skills

Educational Qualification

Bachelors Masters or PhD degree in Computer Science Software Engineering Engineering Data Science Machine Learning or a related technical discipline.

Minimum 8 years of industry experience including significant hands-on delivery across both software engineering and AI/ML-enabled product development.

Required Skills

Strong experience delivering production-grade digital products with a balanced focus on modern software engineering and applied AI/GenAI.

8 years of development experience across relevant languages frameworks and tooling such as Python Java JavaScript/TypeScript JVM-based technologies APIs event-driven systems and cloud-native platforms.

Strong software engineering fundamentals including system design clean code practices testing strategies code reviews version control and maintainable architecture.

Hands-on experience building deploying and monitoring applications on Kubernetes and related cloud-native infrastructure.

Experience designing and operating scalable services APIs microservices or platform components with strong attention to reliability performance and security.

Practical experience designing developing deploying and monitoring machine learning and GenAI Software Design Software Engineering Management Software Engineering Process