Role Description As a Junior Software Developer (AI & Agentic Systems), you will design and implement cutting-edge agentic workflows and AI-driven applications. This role sits at the intersection of software engineering, artificial intelligence, and distributed systems—focused on building intelligent automation that empowers users to orchestrate complex tasks seamlessly. You will work closely with product owners, UI/UX designers, and other developers to build and optimize systems that enable autonomous and semi-autonomous agents to interact with data, APIs, and users. The work we do is diverse, challenging, and rewarding. Agility PR Solutions develops state-of-the-art tools that help public relations professionals discover media influencers and derive actionable insights from global media coverage. In this role, you will contribute to both: - Backend systems (Java, big data platforms like Hadoop/Solr) - Modern AI application layers (TypeScript, agent frameworks, LLM integrations) You will solve problems related to large-scale data processing, distributed workloads, and intelligent orchestration, while also contributing to evolving AI-driven product capabilities. At Agility PR Solutions, we value collaboration, curiosity, and continuous learning. You’ll be part of a team that supports growth, knowledge sharing, and innovation. Qualifications - Degree in Computer Science or a related field - Hands-on experience with Java development and REST APIs - Working knowledge of TypeScript / JavaScript - Familiarity with AI/ML integrations, including: - Large Language Models (LLMs) - Agentic frameworks (e.g., LangChain, LangGraph) - Strong problem-solving skills and willingness to learn new technologies - Experience with SQL - Experience with Linux - Experience with Git - Experience with Maven Requirements - Nice to have: - Experience with agent orchestration patterns or workflow engines - Exposure to prompt engineering and evaluation techniques - Understanding of distributed systems or big data technologies (Hadoop, Solr) Benefits - Fully remote work environment - Collaborative culture – and key tools enabling it - Competitive compensation package - Health, Dental & Vision benefits - RRSP matching - Life Insurance - Employee Assistance Program (EAP) - Career Development & Progression opportunities - Paid Vacation, Personal Days and Sick days - Flex Fridays in Summer, Week off between Christmas and New Years' - No Internal Meetings Fridays Compensation for this role is expected to fall within the range of $65,000 - 75,000 annually. The final offer will reflect each candidate’s experience, skills, and internal equity.

• Define enterprise AI architecture, standards, and technology roadmap. • Design and deliver production-ready Generative AI and Agentic AI solutions. • Architect scalable AI platforms leveraging cloud-native technologies and modern data ecosystems. • Lead AI solution design, technical reviews, and architecture governance. • Partner with engineering, data, security, and business teams to deliver enterprise AI initiatives. • Evaluate emerging AI technologies and recommend architecture best practices. • Ensure AI solutions meet security, governance, compliance, and performance requirements. • Mentor engineering teams and drive AI adoption across the organization.

• Architect and build a multi-agent system in production — one capable of safely operating across a business's core tools (ERP, CRM, spreadsheets, calendars, email, analytics, compliance systems) • Build and maintain MCPs (Model Context Protocol integrations) that connect the harness to real business systems • Own production system concerns end-to-end: reliability, observability, permissions, and safe workflow execution — this is a system that will take real actions on customers' data, and the bar for getting it right is high • Since there's no existing playbook here, you'll define scope, make the call on tradeoffs, and drive execution with minimal oversight • Design for the user, not just the architecture — a product-first mindset that prioritizes how this actually gets used over what's technically interesting to build • Proactively identify and raise risks or open questions before they become blockers, and bring structured solutions, not just problems • Keep pace with a fast-moving space — agent frameworks, harness toolkits, MCP standards — and bring in better approaches as they emerge rather than waiting to be told • Work hands-on with tools like Claude Code as part of your own build process

• Architect and ship an agentic page builder • Design autonomous deployment and optimization pipelines • Build AI infrastructure powering merchant-facing workflows • Write code, design systems, and drive architecture decisions • Own outcomes and partner closely with the Engineering Lead and Product Lead • Focus on building a storefront system collaboratively with AI agents