• Build & operate GTM automation systems • Build and operate reliable automation across custom code + orchestration tools (e.g., n8n/Workato/Make), including CI/CD, testing, deployment practices, and runbooks that keep iteration fast and safe • Implement modular, scalable, multi-agent AI systems that operate 24/7 and integrate with marketing platforms (e.g., Customer.io, Marketo, Salesforce, BigQuery) • Own technical direction for GTM automation: design data models, define API contracts, build shared libraries, and maintain reference architectures used across teams • Review code, write tests, and maintain production reliability standards • Operate, enable, and scale GTM workflows • Partner with RevOps, Demand Generation, Regional Marketing, Events Marketing, & SDRs to solve workflow inefficiencies through agent-based solutions with measurable business outcomes • Create reusable workflow templates, playbooks, and “how-to” docs so partner teams can safely self-serve common automations (with clear ownership and measurement) • Provide hands-on technical support and troubleshooting for AI systems across teams • Align AI chatbot systems across multiple teams (Marketing, SDR, Customer Success) to create unified prospect interaction routing. • Build intelligent routing logic that determines when and how to engage human resources in prospect interactions.

• Build & operate GTM automation systems • Build and operate reliable automation across custom code + orchestration tools (e.g., n8n/Workato/Make) • Implement modular, scalable, multi-agent AI systems that operate 24/7 and integrate with marketing platforms • Own technical direction for GTM automation • Partner with RevOps, Demand Generation, Regional Marketing, Events Marketing, & SDRs to solve workflow inefficiencies • Create reusable workflow templates, playbooks, and “how-to” docs • Provide hands-on technical support and troubleshooting for AI systems across teams • Align AI chatbot systems across multiple teams to create unified prospect interaction routing • Build intelligent routing logic that determines when and how to engage human resources in prospect interactions • Create internal training materials, best practices documentation, and scalable frameworks for AI tools • Support ongoing AI adoption through hands-on technical assistance and system optimization

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We're looking for an experienced and passionate Senior Full-Stack Software Engineer to join our data science team. In this high-impact role, you will be instrumental in developing our core operational software. You'll take the lead on building sophisticated systems from the ground up, including: - A complex process scheduler (think dynamic Gantt charts) - A seamless invoicing platform that is critical to our clients' success Beyond these core projects, you will collaborate closely with our scientific teams to: - Build Agentic AI systems - Manage data pipelines - Prepare datasets for machine learning models - Create insightful dashboards to optimize everything from laboratory experiments to commercial-scale manufacturing This is a fully remote position, with the expectation of significant working hours overlapping with the US Central time zone to ensure seamless collaboration. Qualifications - Master’s degree in computer science, Engineering, or a related field from a reputed US/European/APAC University with 2+ years of proven experience as a Full-Stack Developer (or similar role), OR a Bachelor’s degree from a Tier 1 Indian University with 5+ years of experience in related field. - Strong knowledge of Python based back-end languages such as FastAPI, Django, or similar. - Proven experience with cloud services like AWS or similar. - Proven experience of DevOps practices and CI/CD pipelines. - Experience with technologies like Terraform or similar. - Experience with databases like MySQL, PostgreSQL, or similar. - Deep expertise in building complex, UI-heavy, and responsive web applications using React.js, Next.js, Svelte, etc. - Proven experience implementing and customizing complex UI components and data visualization libraries, particularly for scheduling applications (e.g., Gantt charts, timelines). - Familiarity with version control tools like Git. - Excellent problem-solving skills and attention to detail. - Strong communication and teamwork abilities. Requirements - Design, develop, and own our primary web applications, including a complex process scheduler (Gantt charts, calendars), and a full-featured invoicing system using React and Next.js. - Create and maintain robust, scalable backend services and APIs that power our front-end applications and data processing needs. - Build and manage ETL pipelines to ingest and structure the data required for our scheduling, invoicing, and machine learning applications. - Collaborate with design and data science teams to take new features from initial concept through to successful deployment. - Write clean, maintainable, and efficient code, taking ownership of the quality and performance of the features you build. - Actively integrate AI-powered tools into your daily workflow to optimize and speed up tasks such as coding, refactoring, testing, and documentation. - Effectively use Agile practices to plan and track your work. - Be judicious in balancing supporting immediate needs with long term infrastructure requirements. Company Description

• Serve as technical lead for early-stage innovation lab projects, working closely with the CINO and our Product, Design, and Delivery teams to shape technical direction for prototypes and new products and guiding design and implementation decisions. • Mentor engineers and collaborators, sharing best practices and fostering a culture of collaboration, psychological safety, and continuous learning in an agile, experiment-friendly environment. • Enable modern DevSecOps practices such as automated testing, CI/CD, infrastructure-as-code, and secure-by-default engineering. • Participate in business development and strategy efforts (proposals, presentations, etc.), when needed. • Rapidly prototype, validate, and iterate on new product ideas, balancing speed of learning with scalable, maintainable code. • Select and implement modern frameworks (React/TypeScript, Node, Python, etc.) and cloud services (containerized APIs, event-driven services, etc.) that enable fast experimentation. • Identify and mitigate technical risks early; clearly communicate trade-offs to non-technical stakeholders. • Support experimentation with AI-driven capabilities (LLMs, data pipelines, agentic tools) where appropriate. • Contribute reusable libraries, documentation, and internal tools that accelerate future innovation lab projects. • Partner with IT and Security teams to ensure prototypes run in sandboxed, compliant environments suitable for R&D. • In your first 30 days, you will complete new hire orientation training and familiarize yourself with the vision for the innovation lab. • Define the initial platform architecture including portal entry point, identity/auth approach, multi-tenant strategy, API gateway, and service boundaries. • Select foundational technologies (frameworks, languages, hosting environment, auth provider or build approach, database pattern). • Create architecture diagrams and engineering decision records to align with leadership and product direction. • Stand up the initial repo structure, monorepo or polyrepo approach, and foundational CI/CD pipeline skeleton. • Begin coding the Platform Shell / Portal (even if just a Hello World + placeholder UI). • Implement a basic working authentication flow (prototype only) to validate feasibility. • Review existing ideas in Linear and select one to implement as the first platform module and collaborate with the existing engineer to break down and begin implementation. • Partner with the Product Operations Manager to define agile development workflows and engineering rituals. • Begin documenting platform principles such as modularity, API-first, secure-by-default, and observability-ready. • After 60 days, deliver a functional login experience connected to cloud infrastructure. • Implement the first platform module from Linear using the new architecture. • Establish patterns/templates for reusable services or modules. • Deploy the platform scaffold into a development environment with automated deploys. • Refine sprint practices, backlog structure, and definition of done with the Product Operations Manager. • Begin mentoring engineers on using the platform architecture and process. • After 90 days, produce a platform roadmap and demonstrate the platform to leadership, articulating how additional features/products will plug into the foundation. • Deliver a working platform with authentication, portal access, and at least one production-ready module. • Establish guidelines for engineers joining the platform effort (documentation, contribution models, code conventions, etc.). • Enable rapid module creation through established templates and tooling. • Establish early success metrics for delivery velocity, platform adoption, and code quality.