Job Specifications
Client: Ministry of Public and Business Service Delivery and Procurement
Work Location: 5700 Yonge St, Toronto, Ontario, Onsite
Estimated Start Date: 2025-11-03
Estimated End Date: 2026-03-31
#Business Days: 102.00
Extension: Probable after the initial mandate
Hours per day or Week: 7.25 hours per day
Security Level: CRJMC
Must Have
7+ years hands-on Java development in an enterprise environment, including Spring Boot, REST API design, integration patterns, and production support / incident management.
Strong SQL and data handling expertise: capable of analyzing schemas, building optimized queries, integrating APIs with data stores, and enforcing data quality in service logic.
Proven experience supporting applications in production: triaging defects, analyzing incident root cause, applying hotfixes, improving resiliency and performance.
Ability to consume and operationalize AI services: call LLM endpoints, handle prompt/response patterns, enforce guardrails, and log usage safely.
Practical understanding of core ML / LLM concepts (supervised vs unsupervised learning, prompt engineering, retrieval, drift) sufficient to collaborate with data/AI teams and ship AI-enabled features.
Comfort working in a secure, governed environment (privacy, PII protection, access control, auditability).
Description
Responsibilities
Design, build, and maintain secure, scalable Java services and APIs using Spring Boot.
Translate technical requirements into production-grade application code, integration logic, and robust data access layers.
Write clean, testable Java (unit, integration, regression), contribute to CI/CD pipelines, and support automated deployments.
Design, build, and optimize data workflows – including SQL queries, ETL logic, and caching for reliability, integrity, and performance in production.
Collaborate with data engineers and analysts to ensure service-layer alignment with enterprise data models and reporting needs.
Diagnose and resolve production issues (performance, defects, incidents); participate in on-call / support rotations as needed.
Review code, enforce engineering standards, document solutions, and mentor intermediate developers.
Collaborate with architects, QA, product owners, and business SMEs in an iterative / Agile delivery model to plan, scope, and land increments.
Apply AI/ML capabilities (LLMs, retrieval-augmented generation, classic ML models) to enhance existing Java services where appropriate.
Design and consume AI-backed services (e.g., classification, summarization, recommendations, reasoning assistants) through secure REST integrations.
Support model lifecycle activities such as monitoring output quality, drift awareness, and safe, auditable usage of AI features.
General Skills
Strong Java and Spring Boot experience building enterprise services at scale (API design, dependency management, error handling, observability, performance tuning).
Advanced SQL fluency (Oracle, MySQL, PostgreSQL) — complex joins, window functions, data validation, and query optimization.
Working knowledge of data modeling, ETL/ELT pipelines, and API-driven data integration.
Hands-on experience with Git, automated testing, secure coding practices, code reviews, and CI/CD pipelines.
Experience deploying containerized services (Docker) to managed platforms or Kubernetes; comfort with production-grade runtime concerns (logging, metrics, alerts).
Ability to integrate third-party / platform services and expose them through hardened APIs.
Familiarity with responsible use of AI services in production: PII handling, privacy controls, auditability, bias/safety considerations.
Ability to translate business needs into technical designs and incremental deliverables; strong troubleshooting and communication skills.
Asset: exposure to AI/ML development workflows (Python, data prep, prompt design, vector search, etc.); ability to partner with data/AI specialists and embed their outputs in Java services.
Desirable Skills
Integration of AI assistants / co-pilots / LLM features (for example: routing a user request from a Java service to Azure Open AI, Co-pilot, Bedrock, etc.).
Retrieval-augmented generation patterns (prompt construction, grounding with vector stores such as FAISS, pgvector, Azure AI Search).
Experience with analytics and data visualization tools (Power BI, Looker, or Tableau) to surface operational and model KPIs.
Understanding of data governance and quality frameworks (metadata management, lineage, audit trails).
Experience in case management / benefits administration domains (for example, Curam or similar social services platforms).
Experience with secure handling of sensitive client data (privacy, masking, role-based access, audit trails).
Experience And Skill Set Requirements
Technical Expertise – 80%
Enterprise Java delivery: 7+ years building secure, scalable services and APIs using Java and Spring Boot in a production environment.
SQL, data access & integration: Strong experience working wi