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Role: BI Migration Lead

Location: Mississauga, ON

Mode of Work: Remote

Duration: 6-12 months

Job Description:

We are looking to hire strong BI migration specialist to lead the transition of enterprise reporting from IBM Cognos to AWS QuickSight.

Role Summary 

Seeking a BI migration specialist to lead the transition of enterprise reporting from IBM Cognos to AWS QuickSight preferably Owns data model conversion, query migration, and report rebuild end to end, ensuring parity of logic, performance, and user experience post migration.

Key Responsibilities 

• Assess existing Cognos landscape: Framework Manager models, report packages, dashboards, and scheduled outputs 
• Translate Cognos data models into QuickSight datasets, SPICE structures, and calculated fields 
• Migrate report logic, filters, prompts, and drill paths into QuickSight analyses and dashboards 
• Convert Cognos queries and SQL into Quick Sight compatible datasets sourced from the target AWS data layer (Redshift, Athena, RDS, or S3) 
• Rebuild visualizations to match or improve on legacy Cognos reports 
• Validate data accuracy and reconcile output against source reports 
• Optimize SPICE ingestion, refresh schedules, and dashboard performance 
• Document mapping, transformation rules, and migration runbook 

Required Skills 

• 5 plus years in BI and reporting, with hands on Cognos (Framework Manager, Report Studio, Cognos Analytics) 
• Proven Quick Sight build experience: datasets, SPICE, calculated fields, analyses, dashboards 
• Strong SQL and data modeling, including star and snowflake schemas 
• Working knowledge of AWS data services (Redshift, Athena, Glue, S3) 
• Experience with report parity validation and reconciliation 

Nice to Have 

• AWS certification (Data Analytics or Solutions Architect) 
• Python for data transformation and automation 

Soft Skills 

• Self-directed, able to move fast with minimal oversight 
• Clear communicator across client and delivery teams 

Role: Sr Quantexa Developer 

Location: Toronto 4 days a week on site F2F interview required

Background check MANDATORY

Duration: 6+ Months

JOB DESCRIPTION:

We are seeking a skilled Quantexa Developer with strong expertise in data engineering entity resolution and network analytics The ideal candidate will design develop and implement Quantexabased solutions to support fraud detection risk analytics and customer intelligence initiatives
You will work closely with data engineers architects business analysts and stakeholders to deliver scalable and highperformance data solutions

Key Responsibilities

• Design and develop Quantexa data pipelines and entity resolution solutions
• Build and configure Quantexa data models pipelines and scoring logic
• Develop and maintain Quantexa configuration Context Configuration Entity Resolution Analytics scoring
• Implement and manage data ingestion transformation and normalization logic
• Collaborate with stakeholders to translate business requirements into technical solutions
• Integrate Quantexa with big data platforms Hadoop Spark Databricks etc
• Optimize system performance and scalability of Quantexa workloads
• Perform data quality checks validation and troubleshooting
• Support deployment testing and production releases
• Document technical designs workflows and processes

Required Skills  

 Technical Skills

• Strong experience with Quantexa platform latest versions preferred
• Proficiency in Scala or Java Scala highly preferred
• Experience with Apache Spark Big Data ecosystems
• Strong SQL skills and experience with data modelling
• Knowledge of entity resolution graphnetwork analytics
• Experience working with ETL pipelines and data integration

Tools Technologies

• Quantexa Context Data Management Scoring
• Apache Spark  
• Hadoop ecosystem
• Databricks preferred
• Git   
• CICD tools
• REST APIs and microservices architecture nice to have

Domain Experience Preferred

• Financial services banking or insurance
• Fraud detection AML AntiMoney Laundering KYC
• Risk and compliance analytics

Soft Skills

• Strong problem-solving and analytical thinking
• Ability to work in agile environments
• Excellent communication and stakeholder management skills
• Ability to handle complex datasets and business logic

Role Description:
Ensures stability and reliability of Appian systems through RCA, AI-assisted diagnostics, and continuous improvement.
Leads resolution of complex L2/L3 issues using AIOps, predictive monitoring, and intelligent alerting.
Drives problem management via automation, AI-enabled root cause fixes, and self-healing mechanisms.
Enhances performance and scalability using AI-driven optimization and predictive capacity planning.
Governs releases and changes with CoE standards, leveraging AI-based risk assessment and validation.
Contributes to Appian CoE platform management, including governance, reusable components, and standardization.
Designs and integrates AI/GenAI solutions (IDP, NLP, chatbots, decisioning) to enable intelligent automation.
Promotes AI-assisted development and hyperautomation to improve efficiency and reduce manual effort.
Maintains AI-enabled knowledge management (runbooks, documentation) for faster issue resolution.
Mentors team on Appian, AI adoption, and CoE best practices while ensuring security and responsible AI compliance.
Provides leadership updates on system health, risks, and AI-driven optimization opportunities.

Salesforce Functional Analyst
Key Responsibilities

·       Collaborate with business stakeholders to understand business objectives, requirements, as-is and future state business processes and pain points
·       Conduct workshops, interviews and requirement gathering and refinement sessions with Product owners and other relevant stakeholders - including architects and tech leads 
·       Identify and propose best possible Salesforce out of the box solution for the problem statement and if gaps exist, propose suitable custom solution in collaboration with tech lead and UX teams.
·       Prepare and present material to Program Salesforce design authority for review of problem statement and proposed solution options to arrive at the best possible outcome that’s acceptable to business and technology teams
·       Perform POC and impact analysis on existing Salesforce processes, configurations and data and present options to Product Owner 
·       Create functional artifacts such as solution refined Epics, broken down User stories ready for development, functional documentation summarized in confluence page.
·       Participate in all scrum ceremonies and lead squad refinement sessions
·       Support QA by providing functional scenarios, clarifying requirements and reviewing test cases against business needs
·       Assist in defect triage and resolution
·       Ensure compliance with Salesforce best practices and security standards

Skills and Qualifications
o   Relevant college, university, or post-graduate degree in Engineering or related education
o   5+ years of experience working as a Functional Lead in Salesforce and 3+ years experience financial industry
o   Proven experience delivering Salesforce solutions at scale in a highly regulated, enterprise scale environments
o   Deep understanding of banking workflows, customer and product lifecycle and financial compliance
o   Strong experience with Salesforce Financial Services cloud and integration with core banking systems and data lakes
o   Ability to lead conversations with cross functional teams and engage effectively with executives, senior leaders and technical teams
o   Familiarity with Agile delivery, Jira, confluence and DevOps pipelines in enterprise settings

The bridge between humans and AI, responsible for building interfaces and middle-tier services that make agentic systems transparent, intuitive, and responsive.

About the Role

You will design dynamic UIs for human-in-the-loop workflows, build backend microservices that safely route requests to AI systems, and manage complex state across multi-turn conversations and

long-running agent tasks.

• AI-Native Interfaces: Build responsive UIs supporting streaming tokens (SSE), agent tool-use visualization, and real-time reasoning feedback.
• API & Middle-Tier Development: Implement secure microservices that orchestrate requests across RAG, agents, and evaluation layers.
• State Management: Handle complex frontend state for multi-turn conversations, agent workflows, and partial-completion tasks.
• Performance Optimization: Ensure low-latency rendering and smooth UX across varied AI response times.

Required Qualifications

• Expertise in modern frontend frameworks (React, Vue) and backend runtimes (Java, Python).
• Experience building chat interfaces or state-heavy dashboards.
• Strong understanding of web security and API design.

Skillset Requirements

• Frontend Engineering: React/Vue, component architecture, state management, and streaming UI patterns.
• AI-Native UX: Designing interfaces for streaming tokens, agent tool-use visualization, and multi-turn reasoning.
• Backend Microservices: Java/Python runtimes, secure routing, and API orchestration.
• State Management: Redux, Zustand, Vuex, or equivalent for long-running agent tasks.
• Web Security: OWASP, secure API design, auth flows, and safe AI request routing.
• Performance Optimization: Low-latency rendering, concurrency handling, and streaming UI performance.
• Event-Driven UI: SSE, WebSockets, and real-time agent feedback loops.
• Integration with AI Backends: Handling varied response times, partial outputs, and agent state transitions.
• Accessibility & Design Systems: WCAG-compliant, reusable component libraries for consistent AI-native UX.

Ensures stability and reliability of production systems by reviewing fixes, performing root cause analysis, and validating resolutions, while providing feedback during incident reviews.
Leads troubleshooting and resolution of complex production issues (L2/L3), ensuring timely restoration within SLAs.
Proactively monitors applications, identifies anomalies, and implements preventive measures to reduce incidents.
Drives problem management by addressing recurring issues through root cause fixes and automation.
Enhances system performance and resilience through targeted improvements and tuning.
Supports change and release activities to ensure smooth, low-risk deployments.
Collaborates with cross-functional teams to resolve issues effectively and maintain service continuity.
Maintains runbooks and documentation to improve support efficiency.
Drives automation to reduce manual effort and improve response times.
Mentors team members on support best practices and ensure compliance with security and governance standards while providing feedback to leadership on system health and risks.

Role: Automation Quality Engineer

Location: Downtown Toronto, Canada

Duration: 6 months and then keep renewing based on performance/requirements

Please submit profiles within the specified rate range.

Job Description:

• Define comprehensive QA strategies aligned with business objectives and technical roadmaps; develop test plans, test cases, and acceptance criteria in collaboration with product owners, developers, and stakeholders; estimate testing effort and track quality metrics across multiple sprints
• Design, build, and maintain scalable automation frameworks using modern tools (Selenium, Cypress, Playwright, Appium); implement Page Object Model (POM) and data-driven testing frameworks; develop and optimize multi-stage CI/CD pipelines (Jenkins, Azure DevOps) integrating automated tests
• Design and execute comprehensive tests for Adobe Experience Manager Sites and Assets (DAM); validate multi-tenant author/publish architectures, content workflows, and content fragment delivery; test AEM content replication, dispatcher caching, and CDN performance; ensure seamless integration between AEM, commerce platforms, and third-party services
• Execute smoke, functional, regression, integration, system, UAT, end-to-end, and accessibility testing (WCAG 2.0/2.1); manage large-scale test portfolios (500+ to 2,000+ test cases); coordinate cross-browser validation and multi-viewport testing; perform SQL-based backend data validation; lead performance and load testing initiatives
• Lead QA initiatives or mentor team members on automation best practices; collaborate cross-functionally with product managers, developers, architects, UX/designers, and business analysts; communicate test results, defect trends, and quality metrics to leadership; establish coding standards and test quality gates
• Design and deliver quality dashboards covering pass rates, coverage trends, and automation progress; track and report key quality indicators (KPIs) to drive data-driven release decisions; document test execution results, defect reports, and root cause analysis
• Ensure testing aligns with financial services compliance requirements; validate PII handling, data encryption, and secure authentication mechanisms; support accessibility compliance testing; participate in production deployment readiness assessments

What do you need to succeed?

Must-have

• 5+ years of software quality assurance and test automation experience with a focus on technical, automated testing across diverse environments (cloud, web, mobile, APIs)
• 3+ years of hands-on experience with Adobe Experience Manager (AEM) testing or similar CMS platforms
• Proven experience designing and implementing scalable automation frameworks from scratch
• Expert-level programming in Java with proficiency in TypeScript and Python
• Hands-on expertise and champion with Accessibility standards and testing tools
• Hands-on expertise with modern automation frameworks (Selenium, Cypress, Playwright, Appium) and BDD tools (Cucumber, Gherkin)
• Strong experience with API testing (Postman, REST Assured, Karate) and testing REST/GraphQL APIs
• Proficiency with CI/CD platforms (Jenkins, Azure DevOps, GitHub Actions) and DevOps principles
• Hands-on experience with test management tools (JIRA, TestRail, Zephyr, HP ALM)
• Advanced SQL skills for test data management and backend validation; experience with multiple database platforms (MySQL, Oracle, SQL Server, DB2)
• Source code configuration tools expertise (Git, GitHub, Bitbucket)
• Strong understanding of AEM Site & Content architecture, content workflows, and DAM operations
• Experience testing microservices, event-driven architectures, and multi-tenant systems
• Knowledge of financial services industry standards, compliance requirements, and security best practices
• Hands-on experience defining test strategies and approaches for Agile projects
• Excellent leadership, communication, and stakeholder management skills
• Bachelor’s degree in computer science, Information Systems, or related field (or equivalent professional experience)

Nice-to-have

• Certifications: ISTQB, SAFe Practitioner, or Adobe AEM certifications
• Experience with AI-powered test generation, self-healing tests, or GenAI tools (Claude Code, GitHub Copilot)
• Mobile testing expertise with Appium, Espresso (Android), or XCUITest (iOS)
• WCAG 2.0/2.1 compliance validation and accessibility testing tools (Siteimprove)
• Performance testing tools expertise (Apache JMeter)
• Experience managing distributed QA teams or leading enterprise quality programs
• Familiarity with cloud platforms (AWS, Azure) and containerization (Docker, Kubernetes)
• Background in financial services industry and regulatory compliance experience

Job Description:

We are looking to hire QA Engineer at Toronto, ON who has experience with automated testing framework.

Requirements

• Proven experience in QA automation with a strong focus on mobile testing
• Hands-on experience with one or more of:
  • Selenium — browser testing
  • Appium — cross-platform mobile automation
  • Playwright (C#) — web and cross-browser automation
• Solid understanding of testing methodologies (unit, integration, E2E, regression)
• Experience integrating automated tests into CI/CD pipelines (e.g. GitHub Actions)
• Experience with Smart UI / visual regression tools (Percy or similar)
• Familiarity with AI-assisted testing — test generation, self-healing tests, or LLM-based triage
• Exposure to MCP (Model Context Protocol) or agentic tooling in a QA context is a strong plus
• Strong analytical skills and ability to work independently across teams

Responsibilities

• Migrate manual testing flows to automated test suites focused on coverage, repeatability, and speed
• Audit existing manual test cases and prioritize high-impact, regression-prone flows for automation
• Implement maintainable test scripts using XCUITest, Detox, Appium, or Playwright[C#]
• Generate clear test reports (pass/fail, screenshots, logs) on a daily/weekly cadence
• Integrate automated runs into CI/CD pipelines so reports are produced on each build or PR
• Track and report on automation coverage progress over time

Senior Appian Developer*
Toronto, ON Duration:12+Months
Hybrid - 3 days at client office

Skills: Digital : Appian BPM - Business Process Management(BPM) & Appian Workflow, IDP and RPA
Experience Required: 6-8 Years

Role Description:
Ensures stability and reliability of production systems by reviewing fixes, performing root cause analysis, and validating resolutions, while providing feedback during incident reviews.
Leads troubleshooting and resolution of complex production issues (L2/L3), ensuring timely restoration within SLAs.
Proactively monitors applications, identifies anomalies, and implements preventive measures to reduce incidents.
Drives problem management by addressing recurring issues through root cause fixes and automation.
Enhances system performance and resilience through targeted improvements and tuning.
Supports change and release activities to ensure smooth, low-risk deployments.
Collaborates with cross-functional teams to resolve issues effectively and maintain service continuity.
Maintains runbooks and documentation to improve support efficiency.
Drives automation to reduce manual effort and improve response times.
Mentors team members on support best practices and ensure compliance with security and governance standards while providing feedback to leadership on system health and risks.

We're looking for an AI Technical Lead to own the architectural backbone of an enterprise AI ecosystem. The ideal candidate brings deep expertise in RAG systems, agentic orchestration, and LLM internals, and can lead a team of developers while keeping the AI stack scalable, secure, transparent, and production-ready.

What you'll do

• Define and evolve end-to-end architecture for RAG pipelines, agent frameworks, and distributed inference systems with a focus on scalability, latency, and output determinism
• Build custom evaluation harnesses for AI agents, RAG pipelines, and LLM reasoning including domain-specific scoring, adversarial tests, and regression suites
• Continuously integrate cutting-edge AI methodologies including structured reasoning, tool-use optimization, memory systems, and multi-agent collaboration
• Design and enforce AI security practices including jailbreak prevention, prompt-injection defense, secure tool use, and zero-trust agent routing
• Optimize token usage, context windows, and cost-latency trade-offs across AI workloads
• Establish observability practices including tracing, logging, telemetry, and agent-level debugging
• Own CI/CD for model updates, containerization, GPU orchestration, and deployment rollout strategies
• Design guardrails, content-safety policies, and audit and traceability frameworks for regulated deployments
• Coach and mentor developers on AI security, tokenomics, UX patterns, and safe deployment practices
• Establish coding standards and architectural guardrails across the AI engineering team

What you bring

• Proven track record delivering production-grade ML/AI systems in a technical lead capacity
• Strong foundations in vector mathematics, LLM internals, embeddings, agent frameworks, and evaluation science
• Deep understanding of transformer mechanics, attention patterns, tokenization, and inference optimization
• Expertise in distributed systems design including load balancing, sharding, concurrency, and high-availability inference clusters
• Experience with systems-level programming and performance-critical code
• Strong knowledge of responsible AI and governance practices for regulated deployments
• Ability to enforce engineering discipline and code quality across a development team

Nice to have

• Knowledge of Google GECX frameworks
• Prior experience in enterprise AI deployments within regulated industries
• Familiarity with GPU orchestration and large-scale inference optimization

Work setup

• Onsite in Brampton, ON
• 6 to 12 month contract
• English proficiency required