Sr. Software Developer Engineer I

Accountabilities:
The Sr. Software Developer Engineer I will be responsible for designing, developing, and maintaining robust backend systems while driving technical excellence across engineering initiatives. The role requires strong ownership, problem-solving abilities, and collaboration with multiple teams. Design, build, and maintain scalable backend services, APIs, and integrations for SaaS products. Own key technical areas by driving architecture decisions, implementation, testing, and production delivery. Develop high-performance distributed systems capable of supporting large-scale, multi-tenant environments. Build and integrate AI/ML-powered features into production applications. Design and implement REST, GraphQL, or gRPC APIs and backend service architectures. Solve complex technical challenges related to scalability, performance, reliability, and security. Collaborate with Product, Data, ML, and Engineering teams to deliver customer-focused solutions. Mentor engineers through code reviews, technical guidance, and knowledge sharing. Lead complex engineering initiatives and contribute to improving development processes. Implement best practices around observability, automated testing, deployment, and infrastructure management. Support cloud-native development using modern engineering tools and practices. Requirements: The ideal candidate has extensive backend engineering experience, strong system design capabilities, and a proven ability to deliver scalable software solutions. They should have experience working with cloud platforms, AI technologies, and modern development practices. 10+ years of professional software engineering experience with strong backend development expertise. Strong proficiency in backend technologies such as Go, Java, Node.js/TypeScript, Rust, or similar programming languages. Experience building scalable SaaS platforms, distributed systems, backend services, and production-grade APIs. Strong understanding of data modeling, relational databases, caching strategies, and storage systems. Experience with REST, GraphQL, gRPC, and complex integrations. Proficiency in Python and familiarity with data engineering or ML libraries such as Pandas, PyTorch, or similar tools. Hands-on experience integrating AI, ML, or LLM capabilities into production applications. Strong knowledge of cloud platforms such as AWS, GCP, or Azure. Experience with Docker, Kubernetes, CI/CD pipelines, automated testing, and production monitoring. Understanding of authentication, authorization, security, data privacy, scalability, and reliability principles. Experience designing and operating large-scale backend systems handling high traffic or global usage. Proven ability to provide technical leadership, mentor engineers, and influence engineering decisions. Nice-to-have experience with AI-powered SaaS products, LLM workflows, recommendation systems, automation, Kafka/event-driven architectures, MLOps, AI guardrails, Terraform, Prometheus, Grafana, OpenTelemetry, or similar technologies. Strong communication skills with the ability to collaborate effectively across technical and business teams. Benefits: Opportunity to work on innovative AI-powered SaaS products and large-scale engineering challenges. Remote work flexibility with a global, collaborative engineering environment. Chance to contribute to impactful products used by organizations worldwide. Continuous opportunities for professional growth and technical learning. Ability to work with modern technologies across backend engineering, cloud infrastructure, data, and AI. Collaborative culture focused on innovation, ownership, and engineering excellence. Opportunities to mentor others and influence technical direction. Competitive compensation and employee benefits package.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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