Accountabilities:
The Senior Software Engineer – Engineering Enablement will serve as a technical leader responsible for designing, building, and evolving large-scale software platforms that support data, AI, and business-critical applications. This role requires strong engineering expertise, architectural vision, and the ability to influence teams through collaboration and technical mentorship.
Lead the design, development, and evolution of scalable cloud-native data and AI platforms.
Apply platform engineering and MLOps principles to support the full machine learning lifecycle, including data ingestion, model training, deployment, monitoring, and optimization.
Define architecture standards, engineering patterns, and best practices for AI-enabled and distributed systems.
Build, review, maintain, and support production-critical services, APIs, and microservices.
Partner with Data Science, Product, Application, and Analytics teams to translate business requirements into scalable technical solutions.
Own systems end-to-end, ensuring reliability, observability, performance, security, and cost efficiency.
Drive technical direction across teams and contribute to long-term platform strategy.
Mentor engineers through design reviews, code reviews, technical guidance, and knowledge sharing.
Promote engineering excellence by improving development practices, operational standards, and system reliability.
Develop and maintain solutions using modern cloud technologies, automation frameworks, and distributed architectures.
Support continuous improvement initiatives through Agile methodologies, collaboration, and innovation.
Contribute to technical decision-making in complex and ambiguous environments.
Requirements:
The ideal candidate brings extensive software engineering experience, strong expertise in cloud-based platforms, and a passion for building innovative solutions at scale. They should demonstrate technical leadership, strong problem-solving abilities, and the ability to collaborate effectively across multiple disciplines.
8+ years of progressive experience in software engineering or related technical roles.
Bachelor’s degree in a related technical field preferred, or equivalent professional experience.
Proven experience designing and leading large-scale data platforms, AI systems, or machine learning-enabled services.
Advanced proficiency in Python and SQL.
Strong understanding of data structures, algorithms, distributed systems, and software architecture principles.
Deep experience designing cloud-native solutions, preferably with Google Cloud Platform (GCP) and ML platforms such as Vertex AI or equivalent technologies.
Hands-on experience with microservices architecture, REST APIs, Kubernetes, and Kafka or similar streaming technologies.
Experience with CI/CD pipelines, infrastructure as code practices, Terraform, and automated testing frameworks.
Familiarity with developer collaboration tools such as Git, Jira, and Confluence.
Experience working with large-scale cloud infrastructure, large datasets, and mission-critical service-level requirements.
Knowledge of Lean Startup, Agile, or similar software development methodologies.
Strong communication skills with the ability to influence technical decisions across teams.
Ability to work independently, manage ambiguity, and drive solutions in a fast-paced environment.
Experience mentoring engineers and raising technical standards across teams.
Cloud or data engineering certifications are a plus.
Benefits:
Competitive compensation package.
Flexible work environment with remote and office-based opportunities.
Opportunity to work on advanced cloud, AI, and data engineering initiatives.
Collaborative culture focused on innovation, ownership, and engineering excellence.
Professional growth opportunities through technical leadership and mentorship.
Ability to influence enterprise-wide technology strategy and platform evolution.
Supportive environment that values continuous learning and emerging technologies.
Inclusive workplace culture focused on teamwork, respect, and meaningful impact.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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