AI Backend Engineer

We offer the industrys only platform that fuses customer identity and anti-fraud solutions customer identity management identity verification and fraud prevention.

We sell to industries with large consumer-facing businesses such as: banking financial services insurance fintech gaming ecommerce/retail telco / media utilities etc.

About the Role:

As the AI Backend engineerat Transmit Security you will join a team of highly skilled machine learning engineers in developing and deploying advanced AI/ML solutions that power our identity and security products. Youll utilize technical skills to drive innovation ensure delivery of high-impact projects and scale our data-driven capabilities across the organization.

This role requires both strategic thinking and hands-on expertise. Youll be responsible for shaping the data science roadmap mentoring a growing team and collaborating with product engineering and business stakeholders to translate business challenges into practical machine learning solutions.

What youll do:

• Design develop and maintain backend services for AI agents and tool integrations using latest technologies
• Build scalable APIs and microservices that interface with LLMs and AI frameworks
• Implement agent orchestration systems tool calling mechanisms and workflow engines
• Optimize performance and reliability of AI-powered applications at scale
• Develop data pipelines for training evaluation and monitoring of AI systems
• Integrate with various LLM providers (OpenAI Anthropic etc.) and manage API interactions

What youll need:

• Excellent coding skills in Python/TypeScript with at least 5 years of hands-on experience building reliable backend services agents and tooling. Familiarity with modern ML frameworks (e.g. PyTorch TensorFlow Hugging Face) is a strong advantage.
• Experience designing deploying and maintaining production systems that integrate ML components including APIs microservices model serving layers feature pipelines monitoring and CI/CD/MLOps workflows.
• Solid experience with AI related contexts Understanding of prompt engineering and LLM optimization techniques RAG architecture
• Solid understanding of distributed systems concepts performance optimization observability and operating services at scale.
• Strong communication skills with the ability to bridge technical product and business perspectives.
• Prior experience in cybersecurity fraud prevention or identity management is a plus especially with secure system architectures or ML-augmented decisioning systems.

Advantages

• Experience integrating with LLM APIs (OpenAI Anthropic Claude etc.)
• Experience with agent frameworks (LangChain LlamaIndex AutoGPT)
• Background in ML/AI concepts and model deployment
• Experience with message queues (RabbitMQ Kafka) and event-driven architectures
• Experience with function calling and tool use patterns in LLMs

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