NO SUBS, NO Sponsorship, NO subcontract companies.
Senior technical lead with 8+ years of hands-on software engineering plus production AI/GenAI delivery.
Must have strong Python/Java/JavaScript/TypeScript, APIs/microservices, Kubernetes/cloud-native architecture and CI/CD experience, along with hands-on ML, GenAI and RAG implementation.
Must have experience architecting and operating production-grade AI-enabled applications and leading/mentoring engineers.
Automatic rejections reasons candidate not qualified for this role/team:
AI/ML research or data science only; GenAI/LLM experience limited to POCs;
software engineers with no production AI/GenAI experience; prompt engineering only;
no Kubernetes/cloud-native experience;
no API/microservices architecture; primarily managerial candidates who are no longer hands-on;
junior/mid-level engineers
The Sr Tech Lead – Software Engineering & AI will 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 quality standards and can be operated confidently in production.
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 centers of excellence, helping to strengthen engineering capability, reusable patterns, and responsible AI adoption.
Professional Qualifications & Skills
Educational Qualification
· Bachelor's, Master's, 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
Numbers & Facts
Location
Houston, TX
Skills
Application Programming Interface (API)unmatched
Artificial Intelligence (AI)unmatched
Automationunmatched
Cloud Architectureunmatched
Cloud Computingunmatched
Code Reviewsunmatched
Coding Standardsunmatched
Computer Scienceunmatched
Continuous Deployment/Deliveryunmatched
Continuous Improvementunmatched
Continuous Integrationunmatched
Data Scienceunmatched
Engineering Managementunmatched
Information Technology & Information Systemsunmatched