Products — Engineering Karachi, Pakistan
Job Summary
Owns end-to-end delivery of full-stack features across 360factors’ enterprise GRC product suite — Angular front end, Java services, APIs, data, and tests. Assignments move between product lines and modules by business priority, on a live estate with a platform migration underway, so the role is built for someone productive in the first sprint rather than after a long ramp. Delivery output is expected to be multiplied through AI agents, with full personal accountability for what ships.
Key Responsibilities
- Owns end-to-end delivery of assigned full-stack features —frontend, services, APIs, data, and tests.
- Builds and operates multiple AI agents across the SDLC, and reviews everything they produce before it ships.
- Delivers migration and integration work between platform generations without regressing customer functionality.
- Owns triage and root-cause resolution of customer-reported issues on assigned modules.
- Collaborates with product, architecture, QA, and UX on requirements and standards, and documents architecture and decisions as they are recovered or created.
Must-Have Requirements
- Java + Spring Boot: 7+ years backend Java, production ownership of Spring Boot 3.x services (Maven, REST, Flyway); comfortable in older Java codebases too.
- Angular + TypeScript: recent delivery on a current major version with enterprise component and data-grid libraries (PrimeNG, AG Grid or equivalent) and RxJS.
- Relational depth: SQL Server / Azure SQL — or comparable RDBMS depth and able to switch immediately — including multi-tenant design, migrations, and query optimization.
- Workflow engines: BPMN or workflow engine experience (Flowable, Camunda, Activiti or similar), or equivalent configuration-driven platform work.
- AI agents: builds and operates multiple agents across the SDLC to multiply personal output, writes precise token-efficient prompts, and reviews every line before it ships.
- Codebase archaeology: becomes productive fast in large, sparsely documented code written by others — reads source to establish intent, then extends it safely.
Required Skills & Technologies
Strength in the must-haves plus fast ramp-up matters more than coverage of everything below.
- Backend: Java 17/21, Spring Boot 3.x, Spring Cloud, Maven, Flowable 7, Flyway, OpenAPI, Apache POI, Eureka, API Gateway, Zipkin. Legacy core on Java 8 / Ant / Tomcat with Velocity and jQuery.
- Data: SQL Server and Azure SQL with per-tenant projection databases, MySQL and PostgreSQL in older components, Redis, Milvus vectors.
- AI services: Python 3.12 / FastAPI embedding gateways, PyMilvus, OpenAI- and OpenRouter-compatible APIs.
- DevOps + test: GitHub Actions, Docker Compose, Nginx, Azure, Playwright, Karma/Jasmine, JaCoCo and Istanbul coverage gates, Testcontainers, SonarQube.
Modules are migrating off legacy platforms on a committed schedule, so migration and integration work is a large share of the role. Architecture is being reconstructed from source where original authors have moved on — expect to establish intent from code and document what you learn. Modules run inside a host platform shell, so tenant context, permissions, and ACLs are shared concerns. Customers are regulated financial institutions: audit trails, access control, and evidence integrity are functional requirements, and customer-specific customization is routine.
Nice to Have
Atlassian Jira platform customization and administration; Power BI / Microsoft Fabric datasets and embedded reporting; document collaboration protocols; vector search and RAG; legacy modernization delivery; GRC, audit, or banking domain exposure and SOC 2 awareness.
Performance Expectations
- Ramp: shipping production tickets independently within 30 days.
- 95% of committed story points delivered on schedule; defect escape rate 5% or less per release; customer issues triaged within 4 hours. (Industry benchmarks, reviewed monthly.)
Required Behavioral Traits
- Integrity and accountability — honest about status, estimates, and mistakes.
- Openness to new tools, technologies, and challenges; quick to adopt what works.
- Reverse‑engineers product areas that have limited, outdated, or no documentation — reads the source, asks the right questions of the people who still hold the context, and uses AI tooling to reconstruct how something actually works, then writes it down for the next person.
- Dependable and self‑motivated, with strong judgement in ambiguous problems, and clear communication across engineering, QA, UX, and product.
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