Vista previa de la oferta
Senior Software Engineer-AI
senior · Technology / Software Development
Skills and Competencies- 5+ years of software engineering experience designing, coding, testing, and operating production-grade backend services and cloud-native applications
- Strong coding proficiency in TypeScript, Python, C#, or similar technologies, with experience building scalable application programming interfaces, microservices, and distributed systems
- Practical experience building enterprise AI applications using large language models, including agents, retrieval augmented generation, orchestration frameworks, and model optimization
- Demonstrated ability to own services, components, or features end to end, from technical design through production deployment and ongoing operation with limited supervision
- Hands-on experience with cloud-native technologies, serverless applications, event-driven architectures, data pipelines, relational and NoSQL databases, vector databases, observability tooling, and automated deployment pipelines
- Solid understanding of algorithms, data structures, scalability, reliability, performance optimization, security best practices, and engineering trade-offs
- Experience mentoring engineers through code review, pairing, debugging, documentation, and the promotion of engineering excellence through testing and continuous improvement practices
- Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use
- Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience
- Design, code, test, and operate backend services, application programming interfaces, data pipelines, and inference pipelines that support real-time and batch AI workloads
- Own the delivery of assigned features and components end to end, from technical design through deployment, monitoring, production support, and continuous improvement
- Build and enhance large language model application features using retrieval augmented generation, orchestration frameworks, evaluation methods, agentic workflows, and tool integration
- Contribute to technical designs, participate in design reviews, and identify risks, constraints, trade-offs, and alternative approaches
- Maintain engineering excellence through automated testing, code reviews, observability, monitoring, alerting, operational readiness, and participation in on-call support
- Apply machine learning operations practices, including prompt versioning, automated evaluation, deployment pipelines, monitoring, and production issue resolution
- Partner closely with product managers, data scientists, machine learning engineers, and fellow engineers to translate requirements into reliable software solutions
- Mentor engineers, contribute to shared frameworks and developer tooling, document system designs and operational runbooks, and promote responsible AI practices across delivered features