Mumbai, Maharashtra, India
Information Technology
Other
Splunk
Overview
Overview
As a Senior Software Engineer in the Artificial Intelligence group, you will play a vital role in building and optimizing systems that power AI-driven solutions. Your primary focus will be on developing and deploying highly scalable, production-ready backend systems that support AI assistants, statistical models, deep learning frameworks, intelligent agents, and foundational AI services. You will collaborate with machine learning engineers and multi-functional teams to drive standard processes in software engineering, DevOps, Kubernetes-based deployments, and backend service development.
Responsibilities
Design and implement high-performance backend architectures that integrate seamlessly with AI-powered products. Build modular, fault-tolerant, and efficient services to support large-scale AI workloads while ensuring low-latency interactions between data pipelines, inference engines, and enterprise applications.
Enhance scalability by designing distributed systems that efficiently handle AI workloads and inference pipelines.
Supervise Kubernetes-based deployments by developing and maintaining Helm charts, Kubernetes operators, and cloud-native workflows to handle AI model deployment.
Mentor and guide engineers to strengthen team expertise in backend development.
Requirements
6+ years of strong backend experience in Python (preferred) or Java, with expertise in building RESTful APIs, microservices, and event-driven architectures.
Strong background in product development with validated experience in building scalable software solutions, along with hands-on exposure to Kubernetes and CI/CD pipelines for various AI/ML applications.
Proficiency in coding and algorithm development using modern programming languages, particularly Python/Java.
Strong grasp of algorithms and data structures with proven expertise.
Expertise in Kubernetes and container orchestration.
Extensive experience with AWS, GCP, or Azure, including hands-on expertise in cloud-native services for AI workloads (e.g., S3, Lambda, EKS/GKE/AKS, DynamoDB, RDS, etc.).
Exceptional problem-solving skills with the ability to balance scalability, maintainability, and performance trade-offs optimally.
Preferred Experience
Proven product development experience in a product-based organization.
Familiarity with cybersecurity, observability, or related domains to enhance AI-driven decision-making.
Prior experience working with AI/ML pipelines, model-serving frameworks, or distributed AI workloads.
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