Description
We are seeking a Principal Cloud Developer - AI/ML to lead the architecture, engineering, and operational excellence of cloud-native, data-intensive enterprise applications.
Job Description:
As a Principal Cloud Developer - AI/ML, you will own technical strategy, platform scalability, reliability, cloud operations, and engineering excellence while providing hands-on technical leadership.
Key Responsibilities:
- Own end-to-end architecture and technical roadmap for data-intensive and AI-enabled enterprise applications.
- Design scalable, secure, resilient cloud-native solutions for application, data, and AI workloads.
- Lead architecture reviews, technical governance, and technology selection.
- Drive engineering best practices including TDD, code reviews, CI/CD, automation, and MLOps/LLMOps practices.
- Architect data platforms, APIs, microservices, distributed systems, and AI service integration patterns.
- Lead the design and operationalization of AI/ML solutions, including model deployment, monitoring, drift detection, and retraining strategies.
- Evaluate and implement Generative AI use cases such as LLM-powered assistants, RAG architectures, prompt orchestration, and agent-based workflows where relevant.
- Establish observability, monitoring, reliability, incident response, and governance practices for both software and AI systems.
- Mentor engineers and influence technical direction across teams.
- Partner with Product, Security, Infrastructure, Data Science, and Business stakeholders.
What you need to bring:
- 12+ years of software engineering experience.
- 5+ years in architecture or technical leadership roles.
- Expertise in programming languages like Java, Python, or Go, Framework like ReactJS, Angular and NodeJS.
- Strong OOAD, design patterns, microservices, and distributed systems experience.
- Strong API design experience using REST, JSON/XML, Swagger, and Postman.
- Experience with PostgreSQL, SQL Server, Oracle, and exposure to NoSQL databases.
- Experience with Linux/Unix, HTTP, caching, scalability, and performance optimization.
- Agile/Scrum, TDD, unit testing, and troubleshooting expertise.
- Strong understanding of AI/ML fundamentals, model lifecycle, feature engineering, and production deployment patterns.
- Hands-on experience with AI/ML frameworks and platforms such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
- Experience building or integrating Generative AI solutions using LLMs, prompt engineering, embeddings, vector databases, and RAG patterns.
- Knowledge of MLOps/LLMOps practices including model versioning, evaluation, monitoring, experimentation, and governance.
- Ability to assess AI solution trade-offs across accuracy, latency, scalability, security, explainability, and cost.
- Effectively communicate product architectures, design proposals, and negotiate options at business unit and executive levels.
What We Can Offer You:
- Health & Wellbeing
- Personal & Professional Development
- Unconditional Inclusion