Backend AI & Data Pipeline Engineer at Seeka Technology – Islamabad | Jobyssey

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

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