Backend Engineer (Go) – AI Security Platform
Backend engineer building production Go services for a greenfield AI-security platform that protects AI agents and LLM-powered applications at a global cybersecurity company hiring via Pragmatike. Core stack: Go, Python, gRPC/REST, Kafka-style event streaming, Kubernetes, and AWS/GCP/Azure; remote-first within India.
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Middle
- Employment
- Full time
- Experience
- 2+ years
- Category
- Backend
- Posted
Skills
Must have
- 4+ years professional backend engineering experience, including 2+ years building production services in Go (senior: 6+ overall, 3+ in Go)
- Strong understanding of Go concurrency, networking, and performance (goroutines, channels, context, profiling)
- Working knowledge of Python
- Experience designing gRPC and REST APIs, working with protobuf, and building asynchronous/event-driven systems such as Kafka
- Experience with Docker, Kubernetes, and at least one major cloud provider (AWS, GCP, or Azure)
- Experience with relational and/or NoSQL databases in distributed systems
- Strong testing discipline and attention to data correctness
- Fluent English with strong written and verbal communication
- Comfortable using AI coding assistants such as Claude Code, Cursor, GitHub Copilot, or Codex (must-have)
- Ability to work independently and take ownership in a remote-first, distributed environment
Nice to have
- Experience with API gateways, proxies, policy/authorization engines such as OPA or Cedar, or service meshes
- Deep knowledge of a major cloud provider's APIs and IAM model
- Experience with Elasticsearch/OpenSearch, ClickHouse, or other search/indexing and columnar data systems at scale
- Familiarity with LLM agent frameworks, tool-calling protocols, and AI/agent security
- Experience building multi-tenant SaaS platforms
- Background in cybersecurity, security tooling, or trust & safety
- Experience introducing AI-assisted or agentic development workflows across engineering teams
Full description
Location: India, Remote-First
Employment: Full-Time
Start Date: November 2026 onward, with staggered start dates
Experience: Mid-Level to Senior
Language: Fluent English required
Industry: Cybersecurity / Enterprise SaaS / AI Security
About the Opportunity
Pragmatike is recruiting on behalf of a global enterprise cybersecurity company building a new generation of products to secure AI agents, LLM-powered applications, and the data they access.
The engineering organization is scaling rapidly in India, with multiple Backend Engineer openings across several product workstreams.
Depending on your experience and interests, you may join one of the following areas:
- Agentic Security: Real-time policy enforcement for AI agent actions, tool calls, and data access.
- AI Security Gateway: High-performance proxy between enterprise applications and LLM providers, covering inline inspection, DLP, rate limiting, and streaming.
- Platform: Shared multi-tenant foundations including identity/RBAC, configuration, event streaming, storage, and internal APIs.
- Data Security Integration: Event-driven integrations between AI security products and existing data security infrastructure.
- Cloud Discovery: Services that discover AI agents, model endpoints, and AI-enabled applications across AWS, Azure, and GCP, and map their access.
- Agentic AI Forensics: Ingestion, indexing, and querying of agent traces and security events for investigation and analysis.
- AI Risk Research: Tooling and testing harnesses that enable security researchers to identify and validate attacks against AI agents.
Across all workstreams, the core stack includes Go, Python, gRPC/REST, event streaming, Kubernetes, and major cloud platforms. AI-assisted development is also a core part of the engineering workflow.
What You'll Do
- Design, build, and operate production Go services with high standards for performance, reliability, and multi-tenancy.
- Design APIs and data models, owning service contracts, idempotency, retries, and back-pressure.
- Build event-driven pipelines and integrations with cloud providers, internal systems, or AI/agent frameworks.
- Own service reliability through testing, observability, CI/CD, and production readiness.
- Use Python for tooling, testing, migrations, automation, or data workflows.