Platform AI/ML Software Engineer

About the role

Future Secure AI is looking for a senior engineer to join our core platform team to build and scale the infrastructure behind our intelligent enterprise interactions. You will work on the systems that allow our AI models to function at scale while creating high-quality tools for developers.

Key facts

What you'll do

• Architect and maintain the primary components of the FutureSecure.ai platform with a focus on performance and reliability.
• Create and refine integrations for large language models, covering token management, streaming, tool usage, and prompt engineering.
• Build distributed systems that utilize idempotency, durable execution, circuit breakers, and retry logic.
• Design and manage SDKs and internal tooling that prioritize developer experience and clear API documentation.
• Manage cloud environments on AWS, Azure, or GCP using native patterns and managed services.
• Operate and scale services using Kubernetes and Docker.
• Audit the full stack to find and resolve performance bottlenecks.
• Partner with researchers and engineers to maintain high standards for testing and code quality.

Requirements

• Bachelor degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
• Minimum of 5 years of professional experience in a similar engineering role.
• Proficiency in TypeScript/Node.js and at least one compiled language such as Go, Rust, or C++.
• Proven ability to design distributed systems using concepts like circuit breakers, retry semantics, idempotency, and durable execution.
• Experience managing cloud infrastructure and services on AWS, Azure, or GCP.
• Practical experience deploying and scaling containerized applications with Kubernetes and Docker.
• Background in creating developer-facing SDKs or platform tools with a focus on API design.
• Broad interest in computer systems, including networking, databases, operating systems, security, and compilers.

Nice to have

• Knowledge of LLM integration patterns, specifically streaming, tool use, token management, and prompt engineering.

Skills & tools

• TypeScript, Node.js, Rust, Go, C++, AWS, Azure, GCP, Docker, Kubernetes, Distributed Systems, LLMs.

Practical notes

• We manage our hiring process internally and do not accept inquiries from recruitment agencies. Please apply directly through our company website.