Senior Software Engineer (AI)

Gamer2Gamer; Kuala Lumpur; On-site; MYR 180,000 - 240,000; Full time

Job summary

Jora Malaysia is seeking a Senior Software Engineer to design, build, and ship AI-powered products across our fintech portfolio, including eKYC identity verification and fraud detection. You will own architecture decisions, mentor teammates, and focus on scalable, production-ready systems leveraging AWS serverless, Bedrock, and LLMs.

You will collaborate with product and QA teams to deliver compliant, high-quality software and drive continuous improvement in CI/CD, observability, and cost

Qualifications

• 3+ years of backend or full-stack engineering experience, including 2+ years hands-on work with AI/ML or LLM systems in production.
• Strong Python skills, with experience in NoSQL databases, REST APIs, and AWS serverless architecture.
• Demonstrated experience building LLM-based solutions: prompt engineering, agent-style architectures, and integration with providers such as AWS Bedrock, OpenAI, or Anthropic.
• Experience evaluating and monitoring AI systems — automated testing, quality metrics, and production observability.
• Proven track record designing scalable APIs and distributed systems.
• Understanding of applied ML integration (OCR, biometrics, document validation, or fraud/anomaly detection).
• Excellent problem-solving skills; able to translate technical decisions into business impact.
• Strong written and verbal communication skills, capable of explaining complex technical concepts to non-technical stakeholders.
• A team player who thrives in a collaborative, idea-driven, Agile environment, balancing hands-on coding with technical leadership.
• Actively follows AI advancements and industry best practices.

Responsibilities

• Design and implement end-to-end AI systems — inference pipelines, agent workflows, and tool-calling architectures — from design through production readiness.
• Build LLM-powered features on AWS Bedrock: context orchestration, system prompts, memory, retrieval (RAG), and structured inputs/outputs.
• Develop and optimize ML components for identity verification and fraud detection (OCR, face matching, anomaly and spoof detection).
• Build, scale, and secure microservices on AWS serverless (Lambda, API Gateway, DynamoDB, S3, Bedrock).
• Own evaluation frameworks, guardrails, and AI observability — logging, tracing, quality monitoring, and latency/cost-aware fallback strategies across models and providers.
• Oversee model deployment and performance monitoring for ML and LLM components in production.
• Contribute to the technical roadmap; drive architecture decisions aligned with product and compliance goals.
• Evaluate and integrate third-party services — verification vendors, OCR engines, biometric SDKs, and LLM providers — as needed.
• Collaborate with Product Owner, BAs, UX/UI designers, and QA to deliver seamless product experiences.
• Mentor engineers through code review, pairing, and enforcing development best practices; drive continuous improvement in CI/CD, observability, and cost efficiency.
• Ensure compliance with PDPA, PCI DSS, and other relevant standards, including responsible AI practices.

Skills

Python

NoSQL databases

REST APIs

AWS serverless

LLM/AI systems

Distributed systems

Problem-solving

Communication skills

Agile team

Tools

AWS Bedrock

OpenAI

Anthropic

Docker

Kubernetes

Job description

Jora Malaysia will close on 9th September 2026. Thank you for being with us, we are cheering you on as you continue your career journey.

We are seeking a hands-on Senior Software Engineer to design, build, and ship AI-powered products across our portfolio — including eKYC identity verification, fraud detection, and AI agent chatbots. This is a senior individual-contributor role with strong technical leadership: you will own architecture decisions, set the engineering bar, and mentor teammates, while spending most of your time building. You will work in a small, talented squad creating systems that combine AWS serverless technology, large language models, and machine learning within a regulated FinTech environment.

Responsibilities

• Design and implement end-to-end AI systems — inference pipelines, agent workflows, and tool-calling architectures — from design through production readiness.
• Build LLM-powered features on AWS Bedrock: context orchestration, system prompts, memory, retrieval (RAG), and structured inputs/outputs.
• Develop and optimize ML components for identity verification and fraud detection (OCR, face matching, anomaly and spoof detection).
• Build, scale, and secure microservices on AWS serverless (Lambda, API Gateway, DynamoDB, S3, Bedrock).
• Own evaluation frameworks, guardrails, and AI observability — logging, tracing, quality monitoring, and latency/cost-aware fallback strategies across models and providers.
• Oversee model deployment and performance monitoring for ML and LLM components in production.
• Contribute to the technical roadmap; drive architecture decisions aligned with product and compliance goals.
• Evaluate and integrate third-party services — verification vendors, OCR engines, biometric SDKs, and LLM providers — as needed.
• Collaborate with Product Owner, BAs, UX/UI designers, and QA to deliver seamless product experiences.
• Mentor engineers through code review, pairing, and enforcing development best practices; drive continuous improvement in CI/CD, observability, and cost efficiency.
• Ensure compliance with PDPA, PCI DSS, and other relevant standards, including responsible AI practices.

Requirements

• 3+ years of backend or full-stack engineering experience, including 2+ years hands-on work with AI/ML or LLM systems in production.
• Strong Python skills, with experience in NoSQL databases, REST APIs, and AWS serverless architecture.
• Demonstrated experience building LLM-based solutions: prompt engineering, agent-style architectures, and integration with providers such as AWS Bedrock, OpenAI, or Anthropic.
• Experience evaluating and monitoring AI systems — automated testing, quality metrics, and production observability.
• Proven track record designing scalable APIs and distributed systems.
• Understanding of applied ML integration (OCR, biometrics, document validation, or fraud/anomaly detection).
• Excellent problem-solving skills; able to translate technical decisions into business impact.
• Strong written and verbal communication skills, capable of explaining complex technical concepts to non-technical stakeholders.
• A team player who thrives in a collaborative, idea-driven, Agile environment, balancing hands-on coding with technical leadership.
• Actively follows AI advancements and industry best practices.

Nice to have:

• Experience building or maintaining Retrieval-Augmented Generation (RAG) systems, including vector databases and embedding pipelines.
• Familiarity with AI guardrails, model safety measures, or responsible AI best practices.
• Familiarity with KYC/eKYC, FinTech, or RegTech domains.
• Experience fine-tuning LLMs or building automated AI training pipelines.
• Node.js, Docker, or containerized deployment experience.