Mistral AI Studio Engineer

Role Summary
We are looking for an AI Engineer with hands-on experience in building, integrating, and deploying Generative AI solutions using Mistral AI Studio and Mistral APIs. The ideal candidate should have strong experience in LLM application development, prompt engineering, RAG, AI agents, tool/function calling, model evaluation, API integration, and production deployment of AI solutions.

The role will involve designing and building enterprise-grade AI applications that leverage Mistral models for automation, knowledge search, document understanding, customer support, workflow automation, and domain-specific AI assistants.

Key Responsibilities

• Design, develop, and deploy AI solutions using Mistral AI Studio, Mistral APIs, and related LLM capabilities.
• Build AI agents using Mistral s Agents and Conversations API, including tool usage, function calling, handoffs, and multi-step workflows.
• Develop Retrieval-Augmented Generation solutions using enterprise documents, knowledge bases, vector databases, and document search.
• Create reusable prompts, prompt templates, system instructions, and evaluation datasets for enterprise use cases.
• Integrate Mistral AI models with business applications, APIs, databases, CRM, ERP, ticketing tools, document repositories, and workflow systems.
• Build AI-powered solutions for document processing, summarization, classification, Q&A, content generation, and decision support.
• Implement guardrails, moderation, privacy controls, access controls, and responsible AI practices.
• Evaluate model responses for accuracy, hallucination, relevance, safety, and business usefulness.
• Support model selection, prompt tuning, performance optimization, token/cost optimization, and latency improvement.
• Work with cloud platforms such as Azure, AWS, or Google Cloud Platform for deployment and integration.
• Collaborate with business stakeholders, data teams, architects, and application engineering teams to convert business requirements into AI solutions.
• Prepare technical documentation, architecture diagrams, deployment guides, and knowledge-transfer materials.

Required Skills

• Hands-on experience with Mistral AI Studio, Mistral API, or similar LLM platforms.
• Strong understanding of Generative AI, LLMs, prompt engineering, AI agents, RAG, and embeddings.
• Experience with Python and API-based application development.
• Experience building AI applications using frameworks such as LangChain, LlamaIndex, Semantic Kernel, or similar.
• Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Azure AI Search, OpenSearch, or similar.
• Strong understanding of REST APIs, JSON, authentication, and backend integration.
• Experience with document ingestion, chunking, embedding, retrieval, reranking, and response generation.
• Ability to evaluate LLM outputs and create test/evaluation frameworks.
• Good understanding of cloud deployment, CI/CD, monitoring, logging, and application security.
• Strong analytical, problem-solving, and communication skills.

Preferred Skills

• Experience with Mistral agents, function calling, document libraries, OCR, workflow automation, or evaluation capabilities.
• Experience integrating AI solutions with enterprise systems such as Salesforce, ServiceNow, SharePoint, Google Drive, Microsoft 365, SAP, or custom applications.
• Experience with Azure OpenAI, OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, or open-source LLMs.
• Knowledge of Docker, Kubernetes, FastAPI, Flask, or Node.js.
• Experience with LLMOps, model monitoring, prompt/version management, and observability.
• Experience with data engineering, SQL, Snowflake, Databricks, or cloud data platforms.
• Familiarity with responsible AI, data privacy, compliance, and enterprise governance requirements.

Qualifications

• Bachelor s or master s degree in computer science, Data Science, Artificial Intelligence, Engineering, or related field.
• 4+ years of software engineering, data engineering, or AI/ML engineering experience.
• 1+ year of hands-on Generative AI / LLM application development experience.
• Prior experience building production-grade enterprise AI solutions is strongly preferred.

Key Use Cases

• Enterprise knowledge assistant
• Customer support AI assistant
• Document processing and summarization
• RAG-based search and Q&A
• Workflow automation using AI agents
• AI-powered reporting and analytics assistant
• Compliance, policy, and contract review automation
• Internal productivity and operations automation

Success Measures

• Ability to deliver reliable, secure, and scalable AI applications.
• Improved automation and productivity for business users.
• Reduced manual effort through AI-assisted workflows.
• High-quality model responses with strong accuracy, relevance, and governance.
• Smooth integration with enterprise applications and data sources.