Product Engineer (Full Stack, IC)

Accountabilities: Work directly with operational stakeholders to understand workflows, constraints, and business needs, translating them into clearly scoped and buildable solutions. Own features end to end, covering data modeling, backend and frontend development, deployment, instrumentation, monitoring, and post-launch iteration. Build and integrate GenAI-powered capabilities, including LLM integrations, agents, retrieval-augmented generation (RAG), and workflow automation where they can deliver measurable improvements. Use AI-assisted development tools, including coding agents and AI-powered code review, as part of the standard software development workflow. Make pragmatic engineering trade-offs by shipping focused solutions, measuring outcomes, gathering feedback, and iterating quickly. Maintain ownership of production reliability through testing, code reviews, monitoring, production support, and proactive technical-debt reduction. Communicate progress, technical trade-offs, scope decisions, and potential risks clearly to non-technical stakeholders. Collaborate with operational teams to continuously improve products based on real user needs and production insights. At the Senior level, lead ambiguous, multi-stakeholder projects and provide technical guidance and mentorship to other engineers. Requirements At least 4 years of professional software engineering experience. Strong full-stack development skills, with backend experience in Python and preferably Django. Strong frontend development experience with React; experience with Angular or Vue is also acceptable. Solid knowledge of SQL and data modeling. Hands-on production experience with a major cloud platform, preferably GCP, including deploying, operating, monitoring, and debugging services. Practical GenAI experience, including having built at least one feature or tool using LLM APIs, with exposure to prompting, tool use, retrieval, or evaluation. Regular use of AI-assisted coding and development tools in day-to-day engineering work. Demonstrated experience shipping products end to end, including defining requirements directly with business or operational users. Strong product mindset and ability to make effective technical decisions based on user needs and measurable outcomes. Clear, direct communication skills, particularly when working with non-technical stakeholders. Strong ownership, autonomy, problem-solving abilities, and comfort working with ambiguity. Experience with Kubernetes, particularly GKE, and CI/CD pipelines is a plus. Experience with Learning Management Systems, especially Canvas, is desirable. Familiarity with BigQuery, analytics pipelines, or event instrumentation platforms such as Segment is an advantage. Experience with agent frameworks or Model Context Protocol (MCP) is a plus. Experience refactoring complex systems or decomposing monolithic applications is desirable. Candidates must reside in India and be authorized to work in India. Benefits Fully remote position based in India. Opportunity to work directly with operational teams and see the impact of products in real-world use. Significant ownership across the complete product development lifecycle, from discovery and design through deployment and iteration. Hands-on opportunities to apply Generative AI to practical challenges. Short feedback loops with the people using the products you build. Opportunity to work on products that support thousands of learners and contribute to workforce development. Collaborative environment focused on autonomy, pragmatic engineering, continuous learning, and measurable outcomes. Opportunities for senior engineers to lead complex initiatives and mentor colleagues.