Lead the design and implementation of APIs, SDKs, and middleware to integrate AI platform services into Keysight’s software ecosystem.
Collaborate with product teams across T&M, EDA, and LLM frameworks to understand integration requirements and deliver tailored solutions.
Build robust interfaces for model deployment, inference, and monitoring within existing software stacks.
Ensure compliance with security, performance, and usability standards across all integration points.
Mentor junior engineers and contribute to architectural decisions for scalable AI service delivery.
Work closely with MLOps and data engineering teams to align infrastructure with product needs.
Qualifications
Strong programming expertise in Python and C++, with demonstrated experience building production-grade APIs and microservices.
Deep understanding of distributed systems and service-oriented architecture, including experience with gRPC, RESTful APIs, and message queues (e.g., Kafka, RabbitMQ).
Hands-on experience with containerization and orchestration, including Docker, Kubernetes, and Helm for scalable deployment across hybrid environments.
Proficiency in CI/CD pipelines using tools like GitLab CI, Jenkins, or ArgoCD, with a focus on automated testing, deployment, and rollback strategies.
Experience integrating ML models into software products, including model serving (e.g., TorchServe, Triton), inference optimization (e.g., ONNX, TensorRT), and runtime monitoring.
Familiarity with cloud-native development on AWS or Azure, including IAM, networking, and cost optimization strategies.
Strong debugging and performance profiling skills, with experience using tools like Valgrind, perf, gdb, and Prometheus/Grafana for observability.
Working knowledge of secure software development practices, including authentication, authorization, and data protection in AI workflows.
Preferred Qualifications
Familiarity with Keysight’s AI platforms (e.g., Melody, Nexus, TAP) or similar modular AI systems
Exposure to explainable AI, reinforcement learning, or physics-informed ML models.
Strong communication skills and ability to work across globally distributed teams.
