CLOUDESIGN TECHNOLOGY
AI Engineer - AI Ecommerce Shopping Assistance - Python & Typescript
Builds and operates production AI features for e-commerce shopping: Python-based LLM agent runtimes (tool calling, RAG, streaming) plus TypeScript frontends, LLM evaluation harnesses, and cloud deployment/observability, including virtual try-on and multimodal shopping experiences.
- Compensation
- Not disclosed
- Location
- Pune, Maharashtra, India
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Full time
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Strong hands-on experience with Python and TypeScript
- Production experience building LLM-powered applications with tool/function calling, structured outputs, streaming, retries, context management, and RAG
- Strong understanding of asynchronous Python, REST APIs, SSE, and event-driven communication
- Experience designing LLM evaluation frameworks, test datasets, automated graders, regression testing, and evaluation metrics
- Experience deploying and operating cloud-based applications, containerised services, CI/CD pipelines, and infrastructure as code
- Familiarity with production observability, distributed tracing, structured logging, performance monitoring, and incident management
- Experience with caching, latency optimisation, token/inference cost management, feature flags, and safe deployment strategies
- Strong software engineering fundamentals, debugging skills, and end-to-end ownership of production features
Nice to have
- Experience with agent frameworks such as Google ADK, LangGraph, or Claude Agent SDK
- Hands-on exposure to Google Cloud Platform, Vertex AI, Gemini, FastAPI, and Cloud Run
- Experience with frontend frameworks and tools such as Lit, Next.js, esbuild, and Vitest
- Familiarity with PostgreSQL, BigQuery, OpenTelemetry, Opik, and LLM tracing platforms
- Knowledge of MCP servers, sub-agents, agent-to-agent integrations, and retrieval systems
- Experience with e-commerce search, multimodal AI, image generation, virtual try-on, and third-party web embeds
- Understanding of prompt-injection mitigation, multilingual applications, and inference performance optimisation
- Effective use of AI coding assistants and developer productivity tools
Full description
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Focus: Agentic AI, AI Shopping Assistants & Virtual Try-On
Role Summary
We are looking for a Full-Stack AI Engineer to build, deploy, and operate production-grade AI applications, including agentic shopping assistants and multimodal AI experiences. The role requires strong hands-on expertise in Python, TypeScript, LLM-based applications, real-time streaming, evaluation, and cloud infrastructure.
The ideal candidate can independently deliver end-to-end features across backend agent runtimes and frontend interfaces, with a strong focus on reliability, latency, cost optimisation, and production performance.
Key Responsibilities
- AI Agent Development: Build and maintain Python-based agent runtimes using LLMs, tool calling, structured outputs, retrieval-augmented generation (RAG), multi-turn state, and human escalation workflows.
- Full-Stack Engineering: Develop asynchronous Python APIs and TypeScript web components, implementing server-sent events (SSE), streaming interfaces, interactive product cards, and resilient client-side error handling.
- LLM Evaluation: Build evaluation datasets and automated test harnesses using deterministic and model-based graders, regression gates, ablation studies, and pass@k/pass^k metrics.
- Performance & Cost Optimisation: Improve response latency, time to first token, token consumption, caching efficiency, context management, and cost per conversation.
- Production Operations: Implement distributed tracing, structured logging, LLM observability, monitoring, incident resolution, feature flags, controlled rollouts, and rollback mechanisms.
- Cloud & DevOps: Deploy containerised services, manage CI/CD pipelines, infrastructure as code, and production workloads on cloud platforms.
- E-commerce AI Integration: Integrate product search, catalogue data, product details, grounded recommendations, and commerce-related event tracking into AI-powered shopping experiences.
- Virtual Try-On & Multimodal AI: Contribute to image-based generative AI applications, including embeddable frontend widgets and scalable backend services.
- Internationalisation & Scalability: Support multilingual experiences, brand-specific configurations, localisation, currency handling, and backward-compatible integrations.
- Cross-Functional Collaboration: Work with product, business, and engineering stakeholders to troubleshoot quality issues and deliver measurable improvements to customer experience and business outcomes.
Essential Skills & Experience
- Strong hands-on experience with Python and TypeScript.