architectural patterns , testing practices , Software Development, Apis, Distributed Systems, Coding Standards, embeddings, knowledge graphs, Retrieval pipelines, semantic models, taxonomies, schema governance, GraphRAG, evidence-based reasoning, AI-enabled platform capabilities, data systems, hybrid search, versioning practices, RAG, Data Validation, ontologies, semantic search

Rust, C++, Oauth2, Saml, Typescript, Gcp, Distributed Systems, Python, AWS, Auth0, session handling, MFA, Go, token issuance, caching strategies, WorkOS, SCIM, Azure IAM, OIDC

Apis, Object Oriented Programming, Testing Frameworks, React, Typescript, Distributed Systems, System Design, AWS, agentic development tools, micro-services, generative AI, Server-Side Rendering, AI-native software engineering workflows, cloud-based environments, CI CD pipelines, micro-frontends

Elk, PostgreSQL, Grafana, Ruby On Rails, Git, Terraform, Docker, Robot Framework, Selenium, Azure, Kubernetes, Python, Cypress

Cloudformation, Network Administration, Dns, Google Cloud, Sql, Nosql, Docker, Terraform, Firewalls, Restful Services, Azure, Python, Kubernetes, AWS, VPCs, Go, AI-accelerated development practices, Acls, peering, subnets

Java, C++, Scala, Python, large-scale distributed systems, Service-Oriented Architectures, SaaS platform

agile environment , Continuous Delivery, Programming Language, Design Patterns, Continuous Integration, non-functional requirements, data-driven web application design and development, object-oriented design

Machine Learning, Recommender Systems, Tensorflow, Numpy, Pandas, Pytorch, Gcp, Docker, Microsoft Azure, Kubernetes, AWS, scikit-learn

Sentry), Observability tools (Datadog, Incident response practices (PagerDuty, Incident.io), Cloud security, Networking, Kubernetes, Core Backend Infrastructure Engineering, Container orchestration, Backend Platform Engineering