Senior AI & Analytics Engineer
New
J
JobgetherAI analytics
Remote opportunity based in IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- At least 6 years of hands-on experience in analytics engineering, data engineering, business or product analytics, applied AI, or a related technical discipline.
- Required Skills
- PythonSQL
Requirements
- Have at least 6 years of hands-on experience in analytics engineering, data engineering, business or product analytics, applied AI, or a related technical discipline.
- Demonstrate strong proficiency in SQL and Python.
- Have experience building and maintaining production-grade data pipelines and analytical datasets beyond exploratory notebooks.
- Have experience designing scalable, end-to-end solutions integrating data platforms, APIs, services, AI components, and user workflows.
- Have practical experience with B2C, product, or customer data and metrics such as retention, conversion, funnel performance, cohort analysis, and customer lifetime value.
- Have hands-on experience building and deploying at least one LLM-powered application used by real users, using techniques such as RAG, tool or function calling, or AI agents.
- Have experience with at least one AI orchestration or agent framework, such as LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, or OpenAI Agents SDK.
- Be familiar with modern data platforms, analytical modeling, and business intelligence tools.
- Have knowledge of AI evaluation, monitoring, guardrails, or responsible AI practices; these are desirable.
- Be able to explain technical architecture, analytical findings, and complex concepts clearly to stakeholders with varying levels of technical expertise.
- Be able to work effectively in a global, remote-first environment using synchronous and asynchronous communication.
Responsibilities
- Build, maintain, and optimize scalable data pipelines, transformations, analytical datasets, and reusable data products using SQL and Python.
- Analyze B2C, product, and customer data to identify trends, performance drivers, behavioral patterns, and actionable business insights.
- Translate business questions into reliable metrics, analytical models, and decision-support solutions.
- Develop a governed metrics layer with consistent definitions for retention, conversion, customer lifetime value, and other core business indicators.
- Design, build, and deploy LLM-powered applications, agents, copilots, and automated analytics workflows using RAG, tool calling, MCP, and agent frameworks.
- Develop natural-language data interfaces that help product managers, analysts, and business users ask questions and receive data-supported answers.
- Create automated workflows for recurring analyses, including performance reviews, anomaly investigation, and funnel diagnostics.
- Integrate data platforms, analytics systems, APIs, AI components, and user-facing workflows into secure, maintainable, production-ready services.
- Evaluate and improve production AI solutions for accuracy, reliability, cost efficiency, monitoring, and safety.
- Work with product, growth, and business stakeholders to understand analytical needs and deliver decision-support solutions.
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