Security Architect

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.
Collaborate with AI engineers, security researchers, and product teams on threat models and enforcement logic.
Use AI coding assistants as part of your daily development, testing, and debugging workflow.

What We're Looking For

4+ years of professional backend engineering experience, including 2+ years building production services in Go. Senior roles require 6+ years overall and 3+ years in Go.
Strong understanding of Go concurrency, networking, and performance, including goroutines, channels, context, and profiling.
Working knowledge of Python.
Experience designing gRPC and REST APIs, working with protobuf, and building asynchronous/event-driven systems such as Kafka or equivalent.
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 skills.
Comfortable using modern AI coding assistants such as Claude Code, Cursor, GitHub Copilot, Codex, or similar. This is a 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.

AI-First Engineering

AI is a core part of how this team builds software.

During the interview process, you'll be asked about how you use AI in real-world engineering: the tools you rely on, how you validate their output, and how AI has changed your development workflow.

We're looking for engineers who use AI as a force multiplier for quality, productivity, and problem-solving, not simply as an autocomplete tool.

Why Join

Build a greenfield product at the intersection of cybersecurity and agentic AI.
Work on Go services operating at enterprise scale and protecting some of the world's largest organizations.
Take ownership of a product workstream and influence architecture from an early stage.
Work alongside a highly technical, distributed engineering team where AI is a core part of the development process.

Pragmatike is committed to a fair, transparent, and inclusive recruitment process. We do not discriminate based on age, disability, gender, gender identity or expression, marital or civil partner status, pregnancy or maternity, race, religion or belief, sex, or sexual orientation.

In accordance with GDPR, your personal data will be processed lawfully, fairly, and securely and used solely for recruitment purposes, including sharing it with our client(s) for employment consideration.

Originally posted on Himalayas

Job Description

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.

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.
Collaborate with AI engineers, security researchers, and product teams on threat models and enforcement logic.
Use AI coding assistants as part of your daily development, testing, and debugging workflow.

What We're Looking For

4+ years of professional backend engineering experience, including 2+ years building production services in Go. Senior roles require 6+ years overall and 3+ years in Go.
Strong understanding of Go concurrency, networking, and performance, including goroutines, channels, context, and profiling.
Working knowledge of Python.
Experience designing gRPC and REST APIs, working with protobuf, and building asynchronous/event-driven systems such as Kafka or equivalent.
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 skills.
Comfortable using modern AI coding assistants such as Claude Code, Cursor, GitHub Copilot, Codex, or similar. This is a 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.

AI-First Engineering

AI is a core part of how this team builds software.

During the interview process, you'll be asked about how you use AI in real-world engineering: the tools you rely on, how you validate their output, and how AI has changed your development workflow.

We're looking for engineers who use AI as a force multiplier for quality, productivity, and problem-solving, not simply as an autocomplete tool.

Why Join

Build a greenfield product at the intersection of cybersecurity and agentic AI.
Work on Go services operating at enterprise scale and protecting some of the world's largest organizations.
Take ownership of a product workstream and influence architecture from an early stage.
Work alongside a highly technical, distributed engineering team where AI is a core part of the development process.

Originally posted on Himalayas

Job Description

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.

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.
Collaborate with AI engineers, security researchers, and product teams on threat models and enforcement logic.
Use AI coding assistants as part of your daily development, testing, and debugging workflow.

What We're Looking For

4+ years of professional backend engineering experience, including 2+ years building production services in Go. Senior roles require 6+ years overall and 3+ years in Go.
Strong understanding of Go concurrency, networking, and performance, including goroutines, channels, context, and profiling.
Working knowledge of Python.
Experience designing gRPC and REST APIs, working with protobuf, and building asynchronous/event-driven systems such as Kafka or equivalent.
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 skills.
Comfortable using modern AI coding assistants such as Claude Code, Cursor, GitHub Copilot, Codex, or similar. This is a 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.

AI-First Engineering

AI is a core part of how this team builds software.

During the interview process, you'll be asked about how you use AI in real-world engineering: the tools you rely on, how you validate their output, and how AI has changed your development workflow.

We're looking for engineers who use AI as a force multiplier for quality, productivity, and problem-solving, not simply as an autocomplete tool.

Why Join

Build a greenfield product at the intersection of cybersecurity and agentic AI.
Work on Go services operating at enterprise scale and protecting some of the world's largest organizations.
Take ownership of a product workstream and influence architecture from an early stage.
Work alongside a highly technical, distributed engineering team where AI is a core part of the development process.

Originally posted on Himalayas

Job Description

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.

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.
Collaborate with AI engineers, security researchers, and product teams on threat models and enforcement logic.
Use AI coding assistants as part of your daily development, testing, and debugging workflow.

What We're Looking For

4+ years of professional backend engineering experience, including 2+ years building production services in Go. Senior roles require 6+ years overall and 3+ years in Go.
Strong understanding of Go concurrency, networking, and performance, including goroutines, channels, context, and profiling.
Working knowledge of Python.
Experience designing gRPC and REST APIs, working with protobuf, and building asynchronous/event-driven systems such as Kafka or equivalent.
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 skills.
Comfortable using modern AI coding assistants such as Claude Code, Cursor, GitHub Copilot, Codex, or similar. This is a 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.

AI-First Engineering

AI is a core part of how this team builds software.

During the interview process, you'll be asked about how you use AI in real-world engineering: the tools you rely on, how you validate their output, and how AI has changed your development workflow.

We're looking for engineers who use AI as a force multiplier for quality, productivity, and problem-solving, not simply as an autocomplete tool.

Why Join

Build a greenfield product at the intersection of cybersecurity and agentic AI.
Work on Go services operating at enterprise scale and protecting some of the world's largest organizations.
Take ownership of a product workstream and influence architecture from an early stage.
Work alongside a highly technical, distributed engineering team where AI is a core part of the development process.

Originally posted on Himalayas