Consultant

Brillio

. Work directly with customers and business stakeholders to understand complex use cases and translate them into AI/GenAI solutions .

Posted 11/6/2026contractRemote • Missouri • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying AI solutions using LLMs and machine learning technologies, with a strong focus on integrating AI capabilities into enterprise applications and workflows. Proficient in prompt engineering, model evaluation, and implementing responsible AI practices.

Highest-signal resume keywords

Python ProgrammingGenerative AI DevelopmentRAG Pipeline ImplementationCloud Platform ExperienceAI Application Integration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPrompt EngineeringModel EvaluationAPI DevelopmentContainerizationVector DatabasesSemantic SearchAI WorkflowsTroubleshootingPerformance Optimization

Soft Skills

Customer-Facing CommunicationStakeholder ManagementProblem-SolvingAdaptability

Tools & Technologies

Azure OpenAIAWSGoogle Cloud PlatformFastAPIDockerKubernetesLangChainPineconeWeaviateTensorFlow

Industry Keywords

AI SolutionsLLMsMLOpsAI GovernanceData Science

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Work directly with customers and business stakeholders to understand complex use cases and translate them into AI/GenAI solutions
Design, develop, and deploy production-grade applications using LLMs and machine learning technologies
Build RAG pipelines using enterprise data sources, embeddings, vector databases, and semantic search
Develop AI agents and agentic workflows, including tool calling, orchestration, memory, and multi-step reasoning
Integrate AI capabilities with enterprise applications, APIs, databases, cloud platforms, and business workflows
Perform prompt engineering, prompt optimization, model evaluation, and guardrail implementation
Develop backend services and APIs using Python, FastAPI, or similar frameworks
Work with LLM platforms and frameworks such as Azure OpenAI, OpenAI APIs, LangChain, LlamaIndex, and Semantic Kernel
Implement vector search solutions using Azure AI Search, Pinecone, Weaviate, FAISS, or similar platforms
Design and implement scalable AI workloads on Azure, AWS, or Google Cloud Platform
Containerize and deploy AI applications using Docker and Kubernetes
Establish LLMOps/MLOps practices for deployment, monitoring, evaluation, observability, versioning, and continuous improvement
Develop proof-of-concepts and convert successful prototypes into production-ready solutions
Troubleshoot AI application issues across models, prompts, retrieval pipelines, APIs, infrastructure, and customer environments
Implement responsible AI practices covering security, privacy, access control, hallucination mitigation, content safety, and data governance
Collaborate with engineering and product teams to incorporate reusable customer solutions and feedback into the broader AI platform

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field
Strong hands-on programming experience with Python
Experience developing production applications using Generative AI and LLMs
Strong understanding of RAG, embeddings, vector databases, semantic search, prompt engineering, and agentic AI
Experience integrating AI applications with REST APIs, enterprise databases, and cloud services
Hands-on experience with at least one major cloud platform: Microsoft Azure, AWS, or GCP
Good understanding of software engineering principles, Git, CI/CD, testing, containerization, and API development
Knowledge of machine learning concepts, model evaluation, inference, and performance optimization
Experience taking AI solutions from prototype/PoC to production deployment
Strong troubleshooting and problem-solving skills
Excellent customer-facing communication and stakeholder-management abilities
Ability to work in fast-paced environments with ambiguous or evolving customer requirements
Preferred: Experience with Azure OpenAI Service, Azure AI Foundry, Azure AI Search, Amazon Bedrock, Google Vertex AI, or similar AI platforms
Preferred: Experience building AI agents, copilots, conversational AI, or autonomous workflows
Preferred: Knowledge of LLM evaluation techniques, observability, tracing, hallucination detection, and AI guardrails
Preferred: Experience with PyTorch, TensorFlow, or similar frameworks