Senior Full Stack Engineer (Python+ React) at Mobility Global in Bengaluru

  • Company: Mobility Global
  • Location: Bengaluru, Karnataka
  • Job type: full time
  • Workplace: hybrid
  • Posted: 2026-09-29

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Job description

This is a frontend heavy role (70%) and 30% backend Why Mobility Global? At Mobility Global, our mission is to provide trusted information that helps billions of people build, sell, and own vehicles with confidence. As we shape the next generation of automotive intelligence through innovation, AI, and industry-leading data, we're creating new opportunities for our customers, our business, and our people. Key Responsibilities Design, build, and own full stack features end to end — responsive React or Angular interfaces backed by FastAPI services, deployed on AWS and used by global automotive OEMs, suppliers, and internal analytics teams. Build the application layer for AI systems — conversational and agentic experiences including retrieval and text-to-SQL pipelines, tool and MCP integrations, streaming interfaces, human-in-the-loop review, guardrails, and observability. Model and query data across multiple stores — write and tune non-trivial SQL, design schemas, and work across relational, vector, and document/NoSQL databases while keeping performance and cost in view at production scale. Work as a force multiplier with AI coding agents — decompose work into agent-ready tasks, write the specs, context, and guardrails that make agents effective, and apply rigorous review so quality and security rise rather than drift. Raise the engineering bar for the team — lead design discussions, review code and agent-generated output, define patterns and reusable components, and mentor engineers on both craft and AI-native ways of working. Partner directly with product, data science, and business stakeholders — shape requirements, prototype quickly, and see features through to measurable adoption in a global, cross-regional organization with real room to grow into technical leadership. Required Qualifications: 5 to 10 years of professional software engineering experience building and operating production web applications, with a Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience. Deep front-end expertise in React — component architecture, state management, TypeScript, performance optimisation, and accessible, responsive UI. Advanced SQL and hands-on experience across multiple database technologies — relational plus at least one vector, NoSQL, or analytical/columnar stores, including schema design and query tuning. Demonstrated experience building AI-powered systems — LLM application development, RAG or agentic patterns, prompt and context engineering, and evaluation or guardrail design — together with daily, fluent use of AI coding agents (Claude Code, Cursor, GitHub Copilot or similar) in a real delivery workflow. Excellent written and verbal communication — able to explain a design decision or a trade-off clearly to engineers, product managers, and non-technical stakeholders alike. Strong ownership and pragmatic judgement — comfortable with ambiguity, able to scope and prioritise independently, and consistently skeptical about verifying AI-generated output rather than accepting it. Collaborative and low-ego — gives and receives direct technical feedback well, mentors generously, and works effectively across time zones in a distributed global team. Preferred Qualifications : Experience taking an AI product from prototype to production — evaluation harnesses, golden datasets, tracing and observability (LangFuse, OpenTelemetry or similar), cost and latency tuning, and safe rollout. Exposure to Angular framework – Any exposure to Angular in addition to React as the primary tech stack is preferred Strong back-end engineering in Python with FastAPI (or equivalent modern async framework) — REST and streaming API design, authentication and authorisation, testing, and CI/CD. Familiarity with agent frameworks and protocols — multi-agent orchestration, MCP servers and tooling, agent SDKs, or serverless agent runtimes on AWS. Cloud and platform depth on AWS — containerized deployment, infrastructure as code, observa

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