• Lead the Vision: Drive the strategy, planning, and roadmap for our AI platform, identifying key opportunities to integrate AI into every stage of the product development lifecycle. • Architect and Build: Design, develop, and maintain a robust and scalable AI platform. This includes creating and managing intelligent agents to automate tasks in areas such as requirements gathering, story creation, development, testing, CI/CD, and observability. • End-to-End Ownership: Take full ownership of AI initiatives, from initial ideation and proof-of-concept to deployment, monitoring, and ongoing support. • Mentor and Collaborate: Serve as a technical leader and mentor to other engineers, evangelizing AI best practices and collaborating with product managers, designers, and other engineering teams. • Drive Operational Excellence: Ensure the AI platform is reliable, observable, and secure. Develop and maintain robust CI/CD pipelines, monitoring systems, and incident response protocols. • Customer-Centric Mindset: Work closely with customer support and product teams to address customer escalations and use feedback to improve AI-driven solutions.

• Design, develop, and implement highly scalable and reliable full-stack applications using Go, Python, Node.js, and relevant front-end frameworks. • Work extensively with AWS Cloud Services, including but not limited to EC2, S3, Lambda, DynamoDB, RDS, SQS, and SNS. • Manage and deploy containerized applications using Kubernetes, ensuring high availability and performance. • Collaborate with product managers, UX/UI designers, and other engineers to translate business requirements into technical solutions. • Write clean, maintainable, and well-documented code, adhering to best practices and coding standards. • Participate in code reviews, providing constructive feedback and ensuring code quality. • Troubleshoot and debug production issues, providing timely resolutions. • Contribute to the continuous improvement of our development processes and tools. • Stay up-to-date with emerging technologies and industry trends, evaluating their potential impact on our products.

• Own end-to-end development of multi-agent AI systems, from architecture and implementation through testing, deployment, and ongoing operation • Build modular, composable agentic systems using orchestration frameworks (LangChain, CrewAI, Anthropic MCP, or similar) that operate 24/7 across teams • Develop reusable agentic skills that agents invoke across interfaces (Slack, dashboards, internal apps, CLIs) • Implement observability and feedback loops including logging, performance metrics, prompt iteration, model evaluation, and cost management • Establish governance and compliance standards for AI workflows including access controls, audit trails, PII handling, and human-in-the-loop escalation paths • Build MCP servers, APIs, CLIs, and microservices connecting AI models to business systems (BigQuery, Slack, CRMs, email, calendars, analytics tools) • Architect data flows for retrieval-augmented generation (RAG), connecting LLMs to internal knowledge bases, customer data, and real-time business context • Build serverless or containerized services (GCP Cloud Functions, Cloud Run) that scale with usage and integrate with Grafana's cloud infrastructure • Partner with RevOps, Demand Generation, Regional Marketing, and SDR teams to scope high-impact automation problems, identify bottlenecks, and build solutions with measurable business outcomes • Design and deploy workflows using orchestration tools (n8n, Workato, or custom platforms) with CI/CD, testing, and production reliability standards • Build systems designed for self-service with documentation, playbooks, and enablement materials that let partner teams operate independently.

• Join our AI team and build the intelligent systems at the core of Cosuno's platform. • AI Agent Development: Build and improve our agentic system that orchestrates multi-step reasoning to navigate the complex, often messy tendering workflow. • Ship end-to-end into the product: Own features from model/agent through API to the TypeScript front-end — backend service, API, and the integration into the web app. • Ranking, Search & Retrieval: Iterate on the ranking and retrieval systems that power subcontractor matching and marketplace search. • Price Prediction: Improve models that estimate fair pricing for construction work, helping users evaluate bids and make better procurement decisions. • Experimentation & Evaluation: Design offline evals, run online A/B tests, and drive metrics-led iteration. • Collaborate across teams: Work with Product, Engineering, and Data to translate business problems into shipped ML/AI features. • Maintain production ML & AI: Monitoring, alerting, and continuous improvement of everything we deploy.