Staff Software Engineer - Infrastructure (AI Native)
- Compensation
- Not disclosed
- Location
- India
- Work setup
- Remote
- Seniority
- Staff
- Employment
- Full time
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Demonstrated experience designing, building, and shipping AI agents or agentic systems that perform meaningful, real-world tasks. Experience limited to AI coding assistants or prompt experimentation i
- Strong understanding of infrastructure fundamentals, including distributed systems, cloud computing, Kubernetes, networking, and production operations.
- Experience taking infrastructure from early development stages to meaningful production scale, with the ability to explain architectural choices, trade-offs, and lessons learned.
- A reliability-focused engineering mindset, with a strong understanding of failure modes, blast radius, operational complexity, resilience, and recovery strategies.
- Ability to troubleshoot complex issues across multiple layers, from application behavior and distributed services to Kubernetes, networking, and cloud infrastructure.
- Experience automating repetitive operational tasks and developing tools or platforms that improve the productivity of other engineers.
- Experience building internal developer platforms or infrastructure systems, such as CI pipelines, artifact storage, package registries, or related tooling.
- Strong technical communication skills, including the ability to produce clear design documents, explain architectural decisions, lead technical reviews, and document operational learnings.
- Staff-level technical leadership skills, including mentoring engineers, influencing engineering standards, and guiding complex projects without relying solely on formal authority.
- Practical understanding of AI agent architecture, including tool usage, workflow orchestration, state or memory management, evaluation, guardrails, and agent reliability.
- Experience with multi-tenant SaaS platforms, infrastructure automation, distributed systems, or production-grade AI agents is particularly valuable.
- Familiarity with technologies such as AWS/EKS, Kubernetes, OpenTofu, FluxCD, Temporal, VictoriaMetrics, ClickHouse, Grafana, Go, or Rust is beneficial. Expertise across the entire stack is not require
- Ability to work effectively in a remote-first, asynchronous environment, taking ownership of technical decisions and collaborating with colleagues across locations.
Full description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer - Infrastructure (AI Native) based in India.
As a Staff Software Engineer, you will shape the infrastructure that powers enterprise AI applications, helping transform innovative solutions into reliable, production-ready systems. You will work across cloud platforms, Kubernetes, distributed systems, deployment pipelines, and observability to build secure, scalable, and cost-efficient infrastructure. A key focus will be designing and shipping AI agents that can execute real infrastructure and engineering workflows autonomously, with appropriate safeguards and controls. You will help establish robust engineering practices, anticipate operational risks, and improve reliability across complex systems. Working in a remote-first, globally distributed environment, you will combine hands-on technical leadership with architectural guidance and mentorship. This is an opportunity to influence how infrastructure and AI-driven engineering operations evolve at scale.
Accountabilities
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Design, build, and improve scalable cloud infrastructure spanning Kubernetes, networking, compute, storage, and distributed systems.
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Identify performance bottlenecks, potential failure modes, operational risks, and infrastructure weaknesses before they affect production environments.
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Strengthen CI/CD pipelines, automated testing, deployment controls, and rollout strategies to support safer, more reliable releases.
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Build and enhance observability capabilities, including monitoring, alerting, distributed tracing, and operational tooling that improves system visibility and troubleshooting.
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Optimize infrastructure performance, reliability, resource utilization, and cloud expenditure.
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Design, develop, and deploy AI agents for infrastructure management and engineering workflows, enabling them to use tools and APIs, execute multi-step tasks, troubleshoot issues, and automate operational activities.
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Establish safeguards for AI agents operating in production, including evaluation frameworks, permission controls, guardrails, observability, state management, and failure recovery mechanisms.
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Build and maintain internal platforms and developer tools that improve engineering productivity, such as package registries, artifact stores, CI systems, and infrastructure automation solutions.
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Lead technical design discussions and contribute to architectural decisions, design documentation, code reviews, and engineering standards.