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AI Solutions Engineer
Verterim, Inc.AI Solutions Engineer developing and deploying intelligent agents across Microsoft’s AI ecosystem. Collaborating within the AI engineering team to address industry and customer-driven needs.
Tech Stack
Tools & technologiesAzureCloudDjangoFlaskJavaScriptNext.jsPython
About the role
Key responsibilities & impact- Design and implement RAG (Retrieval-Augmented Generation) systems for document processing, policy analysis, and compliance automation
- Build and deploy AI applications using Azure OpenAI, Azure AI Foundry, and Azure Cognitive Services
- Develop multi-agent systems using frameworks like AutoGen, Semantic Kernel, or LangGraph
- Create production-grade REST APIs using Python (FastAPI) for AI services
- Implement prompt engineering strategies including few-shot learning, chain-of-thought, and structured output generation
- Integrate AI solutions with enterprise data sources (databases, document repositories, external APIs)
- Optimize LLM performance including context window management, token optimization, and response quality
- Handle LLM security including prompt injection prevention, guardrails, and content filtering
- Deploy and maintain AI infrastructure using Azure services and CI/CD pipelines (Bicep, Azure DevOps)
- Troubleshoot and resolve production issues in AI systems
- Collaborate with front-end teams (Next.js) to deliver complete solutions
- Collaborate with product managers, and business analysts to translate customer needs into actionable AI requirements.
- Contribute to building reusable frameworks, orchestration templates, and integration components for rapid AI solution deployment.
- Participate in code reviews, sprint planning, and Agile ceremonies to ensure consistent quality and high-velocity delivery.
- Assist in preparing technical documentation, deployment guides, and maintenance procedures.
- Work closely with senior engineers to integrate AI models into production applications, ensuring performance, reliability, and scalability.
- Stay current with Microsoft’s evolving AI ecosystem to identify opportunities for improvement and innovation.
- Propose enhancements to existing AI solutions through improved orchestration, automation, or model optimization.
- Participate in internal knowledge sessions to deepen expertise in LLM integration, prompt engineering, RAG implementations, and AI governance.
- Support experimentation with complex multi-agent coordination using AutoGen and Semantic Kernel.
Requirements
What you’ll need- 2+ years of hands-on experience using Azure OpenAI, Azure AI Foundry, and Azure Cognitive Services.
- Strong Python programming skills with production code experience
- Experience building RAG systems with vector databases (Azure AI Search, Pinecone, Weaviate, or similar)
- Working knowledge of LLM APIs (Azure OpenAI, OpenAI) including parameters like temperature, top-p, frequency penalty
- Experience with at least one API framework (FastAPI, Flask, or Django)
- Understanding of embeddings, chunking strategies, and retrieval optimization
- Familiarity with prompt engineering techniques (few-shot, chain-of-thought, structured outputs)
- Experience with async programming in Python
- Basic understanding of Azure cloud services
- Ability to debug and troubleshoot AI systems in production.
Benefits
Comp & perks- Flexible work arrangements
- Professional development opportunities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonRAG SystemsPrompt EngineeringREST API DevelopmentAsync ProgrammingLLM OptimizationDebugging AI SystemsVector DatabasesEmbedding StrategiesAzure Cloud Services
Soft Skills
CollaborationProblem-SolvingCommunication