Careers

Overview

We are seeking a highly skilled Azure AI Engineer who will play a critical role in building Retrieval-Augmented Generation (RAG) systems that transform how organizations access and leverage enterprise knowledge. This is a formative role at Arivue and requires high ownership, technical depth, and a pragmatic approach to solving real business problems. The ideal candidate will bring expertise across Azure AI services (AI Studio, AI Search, OpenAI), prompt engineering, and RAG architecture, with the ability to bridge domain context and cutting-edge AI technology. You will be responsible for the end-to-end lifecycle of AI solution delivery from requirements gathering to production deployment and continuous optimization.

Key Responsibilities

• Lead RAG architecture and implementation, designing retrieval-augmented generation pipelines using Azure AI Studio, Prompt Flow, and Azure OpenAI that enable users to find critical information in seconds instead of minutes.

• Configure and optimize Azure AI Search with vector embeddings, hybrid search, and custom ranking to ensure high retrieval precision for technical documents.

• Engineer prompts and system instructions that understand domain terminology, context, and hierarchies, ensuring answers are accurate, grounded in source documents, and appropriate for technical audiences.

• Build domain-specific context layers, designing data models for hierarchies, taxonomies, and version control that enrich retrieval with operational context.

• Integrate Azure Document Intelligence to parse complex technical PDFs, scanned documents, tables, and diagrams, ensuring all content is properly indexed and searchable.

• Develop evaluation frameworks and quality metrics (precision, recall, answer relevance, groundedness, latency) to continuously measure and improve RAG system performance based on user feedback and production data.

• Deploy AI systems to production on Azure with proper monitoring (Application Insights), cost optimization (caching strategies, model selection), and auto-scaling to handle large query volumes with <2 second response times.

• Collaborate with frontend developers to design APIs that serve AI-generated responses, source citations, confidence scores, and feedback mechanisms to mobile-optimized user interfaces.

• Work directly with subject matter experts to understand operational workflows and translate them into effective AI solutions.

• Build modular, scalable and reusable AI platform components (RAG templates, evaluation datasets, prompt libraries.

• Current knowledge of AI/LLM models and methodologies including fine-tuning and agentic-RAG.

• Document architecture decisions, prompt strategies, and best practices to build organizational knowledge and enable team scaling.

• Architect the data model: Design and build optimized data models, applying best practices for cloud-native data architectures to ensure high performance and scalability.

• Best practices: Strong understanding of AI and Data governance, security best practices, and cloud architecture principles; Implement and enforce data quality checks, validation rules, security, and governance policies throughout the program lifecycle.

• Mentor junior team members: Provide technical guidance and leadership to other engineers on the team.

Qualifications

• 5+ years of overall Data / AI / ML experience, with at least one full life cycle experience focused on LLMs, RAG systems, and production deployments in enterprise or startup environments.

• Strong proficiency in Azure AI Studio, Azure OpenAI (GPT-4, embeddings), Azure AI Search (vector search, hybrid retrieval), and Azure Document Intelligence. You should be comfortable navigating Azure portal, CLI, and designing AI architectures.

• Deep understanding of retrieval-augmented generation patterns — document chunking strategies, embedding models, vector similarity, semantic search, prompt engineering for context injection, hallucination mitigation.

• Writing production-quality code (not just notebooks) for data processing, API development (FastAPI, Flask), and integration with Azure services. Experience with async programming and error handling.

• Demonstrated ability to design effective system prompts, few-shot examples, chain-of-thought reasoning, and output formatting for domain-specific applications.

• API development: Building RESTful APIs that integrate LLMs, handle authentication (Azure AD, OAuth), implement rate limiting, and provide structured responses with citations.

• Evaluation mindset: Experience measuring AI system quality through metrics (MRR, NDCG, answer accuracy) and A/B testing prompt variations and retrieval parameters.

• Cloud deployment: Deploying applications to Azure (App Service, Functions, Containers) with CI/CD pipelines, monitoring, and production troubleshooting skills.

• Communication skills: Strong ability to explain complex AI concepts to non-technical stakeholders and translate business requirements into technical solutions.

• Collaboration: Proven track record of working with cross-functional teams (frontend developers, cloud engineers, domain experts, client stakeholders).

• Problem-solving: A strong ability to analyze complex data problems and devise effective, scalable solutions.

Preferred

• Experience with manufacturing, industrial operations, or technical documentation domains.

• Familiarity with multiple LLM providers and frameworks (OpenAI, Anthropic, LangChain, LlamaIndex, Semantic Kernel).

• Azure certifications: AI-102 (Azure AI Engineer Associate), AZ-900 (Azure Fundamentals), or similar.

• Fine-tuning experience for domain adaptation (not required for initial projects).

• Knowledge of other Azure services: Cognitive Services, Speech Services, Form Recognizer.

• Database design skills (SQL, CosmosDB) for metadata and manufacturing context modeling.

• Data engineering exposure (ETL pipelines, Databricks, data quality) for document processing workflows.

• Experience with vector databases beyond Azure AI Search (Pinecone, Weaviate, Qdrant).

• Broader understanding of Data and AI foundations

• Knowledge of version control systems and CI/CD pipelines for data workflows.

What We Offer

• A dynamic role in a forward-thinking startup focused on creating advanced AI solutions

• Opportunities for professional growth and collaboration on cutting-edge AI technologies.

• Direct client engagement – Collaborate with client executives, conduct discovery workshops, see your AI systems used daily by business users.

• Remote-first culture with flexible hours focused on outcomes, not face-time.

Location

• Role is remote, anywhere in India

If this is you, send us your resume highlighting relevant AI / RAG project experiences to careers@arivueanalytics.com. Please include:

– Links to GitHub/portfolio with RAG implementations or LLM applications

– Brief description of your most impactful AI project and the business outcome it achieved, and your role in it.

– Your experience with Azure AI services specifically (AI Studio, AI Search, OpenAI)

Overview

We are seeking a highly skilled and experienced Senior Data Analyst who will play a critical role in transforming raw data into actionable business intelligence. This is a formative role in a growing startup and requires high ownership, curiosity, and a get-things-done attitude. The ideal candidate will bring expertise across data analytics, visualization (Looker / Power BI), data validation, and metric governance, with the ability to bridge business context and technical execution. You will be responsible for the end-to-end lifecycle of analytics delivery — from defining KPIs to ensuring data reliability and insight adoption.

Key Responsibilities

• Lead analytical design and development efforts, building standardized dashboards and KPI frameworks that support strategic decision-making across functions.

• Create and maintain scalable data models in Looker (LookML) and/or Power BI (DAX / Data Modeling), ensuring consistency of metric logic across both tools.

• Develop and document standardized metric definitions (e.g., conversion rate, retention, revenue per user) and ensure alignment with upstream data models (BigQuery / Databricks / Snowflake).

• Validate data integrity and correctness through SQL-based reconciliation between BI layers and source data systems (e.g., GA4, transactional datasets).

• Collaborate with data engineers to optimize data flows, define semantic layers, and ensure reliable, performant data access for analytics.

• Apply data storytelling principles to communicate insights clearly to stakeholders, enabling faster and better business decisions.

• Drive adoption of dashboards and insights by working closely with marketing, product, and operations teams.

• Establish QA frameworks and automated checks to ensure freshness, completeness, and accuracy of dashboards and analytical models.

• Document all logic, KPIs, and assumptions to build a shared knowledge base and promote transparency.

• Contribute to data reliability and governance practices, ensuring consistency, security, and clarity in analytics..

Qualifications

• Proven experience: 6–10 years of experience in analytics, BI development, and data storytelling in enterprise or startup environments.

• Tools expertise: Hands-on experience in Looker (LookML, PDTs, model optimization) and/or Power BI (data modeling, DAX, performance tuning).

• Data skills: Strong proficiency in SQL, data validation, and business metric design.

• Data modeling: Experience designing and managing semantic models or data marts for self-service analytics.

• Cloud data familiarity: Understanding of BigQuery, Databricks, or Snowflake ecosystems.

• Analytical mindset: Ability to define, calculate, and interpret KPIs in business context.

• Communication skills: Strong ability to explain technical logic to non-technical audiences with clarity and impact.

• Collaboration: Proven track record of partnering with data engineers, analysts, and business stakeholders.

Preferred

• Experience working with GA4, digital analytics, or customer journey data

• Advanced Certifications in analytics/visualizations

• Broader understanding of Data and AI foundations

• Experience with cross-platform BI governance and centralized metric layers.

What We Offer

• A dynamic role in a forward-thinking startup focused on creating advanced Data and AI solutions

• Opportunities for professional growth and collaboration on cutting-edge technologies.

Location

• Role is remote

If this is you, send us your resume highlighting relevant project experiences to careers@arivueanalytics.com.