Staff Software Engineer-AI

Skills and Competencies

• 8+ years of software engineering experience with hands-on design, coding, testing, and operation of scalable backend systems and cloud-native services.
• Expert coding ability in Python, TypeScript, Go, or a similar modern programming language.
• Deep experience with enterprise AI applications, including large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration, evaluation, and model optimization.
• Experience taking AI solutions from prototype to production while balancing performance, scalability, reliability, security, maintainability, and cost.
• Expertise with AWS, Google Cloud Platform, Azure, Docker, Kubernetes, Elastic Container Service, or equivalent production technologies.
• Experience with APIs, distributed systems, event-driven architectures, data pipelines, PostgreSQL, MongoDB, Redis, vector databases, observability, and automated deployment pipelines.
• Ability to influence technical direction, mentor engineers, and remain close to the codebase.
• Expertise in artificial intelligence, AI innovation, risk management, ethical governance, and responsible AI adoption.

Education

• Bachelor's degree or higher in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience.

Responsibilities

• Design, code, and lead delivery of scalable AI platforms and intelligent applications for production use.
• Build backend services, APIs, data pipelines, inference pipelines, and platform capabilities for enterprise AI workloads.
• Implement retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimization, agentic workflows, and tool integration.
• Establish engineering best practices through code reviews, design reviews, automated testing, observability, monitoring, and operational excellence.
• Champion machine learning operations practices, including model lifecycle management, prompt versioning, evaluation, deployment, monitoring, and continuous improvement.
• Partner with product, data science, machine learning, engineering, and business stakeholders on technical solutions.
• Build reusable frameworks, libraries, developer tooling, and platform components that accelerate AI development.
• Evaluate emerging AI technologies through prototypes and production-readiness assessments.
• Mentor engineers through coaching, pairing, reviews, documentation, and example-setting.

About the Team