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We are a global leader in enterprise automation platforms, delivering AI-powered, cloud-native SaaS solutions for mission-critical finance and ERP workflows. Our platform helps the world's leading organizations automate, orchestrate, and optimize complex business processes at scale.
We foster a high-performance engineering culture built on innovation, ownership, and continuous learning.
CTC offered upto 60 LPA
Your Impact
As a Principal Software Engineer, you will be a senior technical authority and platform architect shaping our enterprise-grade SaaS platform. You will:
This is a senior hands-on individual contributor role with broad system ownership and no people management responsibility.
Key Responsibilities
Required Experience & Skills
AI & Automation Exposure (Must-Have)
Good to Have
What Defines Success in This Role
Job ID: 134397745
Skills:
Nlb, Vpc, Lambda, Gcp, Docker, Terraform, Ansible, Python, Golang, AWS, ILB, Generative AI, GKE, TGW, AI ML tools, Cloud Interconnect, Direct Connect, Ncc, Networking Services, Cloud Run, PrivateLink, ALB, Serverless
Skills:
Kubernetes, Java, Java Spring, Ci, Solr, Saas, Paas, Kafka, Iaas, AWS, Lucene, Sns, Python, Sqs, Elasticsearch, REST, cd, OpenSearch, temporal, Flink, application performance monitoring tools, NoSQL databases
Skills:
Software Development, Aws Services, System Design, programming, promise calculation, fulfillment optimization, architecture design patterns, Reliability, e-commerce delivery systems, Scaling
Skills:
API design, Java, Adobe Campaign, System Architecture, Kafka, Salesforce Marketing Cloud, Spring Boot, Microservices, Kubernetes, Docker, Generative AI, LLMs, CDPs, CRM platforms, Braze, CI CD, Optimove, recommendation systems, Analytics, cloud-native technologies, Customer Segmentation, AI-assisted software engineering tools, event-driven systems, Data JPA, personalisation solutions, AI-driven campaign optimisation, NoSQL databases, Security, Spring ecosystem, domain-driven design
Skills:
data warehouses , snowflake , Databricks, Data Governance, Privacy, legal holds, AWS data ecosystem, schema governance, defensible disposal, cloud-native data platforms, enterprise metadata catalog, S3 patterns, Regulatory Requirements, analytics services, lakehouse, distributed computing frameworks, data lakes, records retention, data contracts, modern data platform architectures