Backend AI & Data Pipeline Engineer

About the role We are looking for a Backend AI & Data Pipeline Engineer to own the end-to-end data processing infrastructure that powers Yuzee's intelligent course and job matching platform. You will design and maintain scalable, event-driven pipelines that process tens of thousands of daily records, generate semantic embeddings, and feed a growing knowledge graph used for personalised career pathway recommendations. What you'll do - Design and maintain three distinct processing pipelines — scheduled job ingestion, event-driven course processing, and a periodic knowledge graph builder — each with independent trigger logic and cost controls - Generate and manage semantic embeddings via Amazon Bedrock (Titan v2), index them in MongoDB Atlas Vector Search, and calibrate similarity thresholds to ensure match accuracy - Build and maintain a knowledge graph linking jobs, courses, skills, and industries using FP-Growth association rules and archetype-to-SOC code mapping - Build and improve a two-stage discovery and matching API on AWS Lambda — vector retrieval first, then deep eligibility scoring with LLM re-ranking - Right-size Fargate Spot instances and design resumable processing loops that tolerate interruption, keeping infrastructure costs under control as data volume scales - Maintain and improve daily job scrapers across multiple sources and build institution data scrapers with robust HTML cleaning pipelines What we're looking for - 1+ years of backend engineering experience focused on data pipelines, ML infrastructure, or search systems - Hands-on experience with AWS serverless and container services — Lambda, ECS Fargate, EventBridge, and Step Functions - Strong Python skills — Pandas, async processing, bulk database operations, and text cleaning - Familiarity with vector databases and semantic similarity search; MongoDB Atlas Vector Search experience is a strong plus - Cost-conscious infrastructure mindset — you think in per-record compute costs, free tiers, Spot resilience, and right-sizing - Ability to document and communicate complex architecture clearly to both technical and non-technical stakeholders Nice to have - Experience with knowledge graphs or association rule mining (FP-Growth, Apriori) - Experience using LLMs for re-ranking or eligibility assessment on top of vector retrieval results - Background in edtech, jobtech, or recommendation/matching systems Degree or existing proven experience Benefits - Fully remote / work-from-home position - Some flexibility in working hours, depending on team requirements and deliverables - Hands-on experience working on meaningful backend, data pipeline, and AI-related systems - Opportunity to contribute to a growing platform with real product and engineering challenges - Professional growth in a practical, fast-paced environment - Strong potential for long-term progression based on performance, regardless of location We believe strong early career roles should do more than give someone a job title. They should help people grow into the kind of professionals they want to become. At SEEKA Technologies, we give junior team members meaningful work that builds real capability, sharpens problem-solving, and develops practical experience in fast-moving business and technology environments. Our goal is to help emerging talent strengthen their skills, expand their potential, and prepare for a future shaped by constant innovation across business and IT. SEEKA Technologies (Not Seeka Limited) is a project under its parent organisation, called Fresh Futures Australia, which is an education consultant based in both Australia and Malaysia. We are developing and creating a platform that utilises A.I. to help match students and job seekers to the right opportunities relevant to them from Kindergarten up to the University, along with vocational training centres and language schools, and of course to businesses and companies who need the right candidates. Ou