Backend AI & Data Pipeline Engineer at Lawn Plus Canada

Islamabad, Islamabad, Pakistan -

Full Time

Start Date

Immediate

Expiry Date

04 Jul, 26

Salary

0.0

Posted On

05 Apr, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, AWS Lambda, AWS ECS Fargate, MongoDB Atlas, Vector Search, Data Pipelines, Machine Learning Infrastructure, Semantic Embeddings, Knowledge Graphs, Web Scraping, Pandas, Async Processing, Cloud Infrastructure, API Development, LLM Re-ranking, SQL

Industry

IT Services and IT Consulting

Description

Company Description 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. Our mission is to make it easier for anyone to find, filter and apply to educational institutions and companies in a more seamless manner. We are currently looking to hire a junior Backend AI & Data Pipeline Engineer who wants to build real-world experience in backend systems, data processing, scraping, retrieval, and cloud-based infrastructure. This role is ideal for someone who already has hands-on technical experience and wants to grow further by working on meaningful engineering challenges that support Yuzee’s intelligent matching platform. You will contribute to the systems that process data, power search and matching, and improve the efficiency, reliability, and scalability of our platform. Below are the important details you will need to take note of: English is the primary language used in the role This is a full-time remote/work-from-home position We welcome both local and international candidates Candidates should have a degree or proven practical experience relevant to the role Job Description 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 Qualifications Degree or existing proven experience Additional Information Use this instead: Benefits Fully remote / work-from-home role Flexible working hours within the team’s expected schedule and business needs Opportunity to work on real backend, data, and AI infrastructure projects Exposure to practical engineering challenges in scraping, pipelines, retrieval, and cloud systems Ongoing growth and development within a fast-moving technology environment Opportunity to build long-term value and grow with the company based on performance, including progression and increased responsibility over time A slightly more polished version: 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 If you want it to sound more attractive for hiring, the strongest version would be to add things like: ownership real product impact career growth direct exposure to architecture and scaling decisions

Responsibilities

You will design and maintain scalable, event-driven data pipelines and manage semantic embeddings to power an intelligent matching platform. Additionally, you will build and improve discovery APIs and maintain daily job and institution scrapers.