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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Science Consultant 1 - **Company:** TOPAZ ENGINEERING, INC. - **Location:** Dallas, TX, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Microsoft Azure, Cloud Computing, Cloud Engineering, Computer Programming, Data Mining, Relational Databases, DevOps, Middleware, Github, R (Programming Language), Design of User Interfaces, Human-Computer Interaction, Information Extraction, Python (Programming Language), Machine Learning, Language Modeling, Open Source Technology, Performance Tuning, OpenAI, Requirements Management, SAS (Software), Systems Integration, TypeScript, Enterprise Search, Pinecone, QLoRA, Scripting, Chatbots, Pytorch, LangChain, ReactJS, Retrieval-Augmented Generation, Transfer Learning, Large Language Models, Multi-Agent Systems, Prompt Engineering, Deep Learning, Model Validation, Llamaindex, Agentic-AI, Pgvector, AngularJS, Kubernetes, HuggingFace, CrewAI, Weaviate, AutoGen, Milvus, Graphql, Data Management, Machine Learning Operations, FAISS, Google Gemini, Terraform, Semantic Kernel, Deepseek (AI Talent Sourcing Platform), AI Co-pilot, Jenkins, ChromaDB - **Published:** October 13, 2026 - **Apply:** https://www.careerbuilder.com/job-details/genai-engineer-dallas-tx--92b9d952-3f70-4fbe-bcf4-06ba88a40ff0 ## About the Role * Strong analytical and problem-solving mindset with hands-on model development skills. * Ability to translate business needs into actionable analytics solutions. * Focus on data quality, validation and performance optimization. * Effective collaboration with business and technology stakeholders. * Commitment to continuous learning, knowledge sharing, fostering team development. * Enterprise GenAI and Agentic AI solutions across RAG, AI agents, conversational AI, enterprise search, workflow automation, document intelligence, and AI copilots; comfortable with planner-executor, reflection, multi-agent, and graph-based orchestration patterns. * Hands-on with orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI) and vector databases (Pinecone, Weaviate, Milvus, pgvector, FAISS, ChromaDB, Azure AI Search); working knowledge of grounding, prompt engineering, and context management. * Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data platforms. * Knowledge of AI governance, LLMOps, evaluation, observability, guardrails, model safety, compliance, and cloud-native deployment. * Exposure to open-source LLM ecosystems - Hugging Face, PyTorch, LoRA, QLoRA, PEFT - and models such as Llama, Mistral, Gemma, DeepSeek, and Falcon. * Familiarity with multimodal AI, including vision-language models, speech and audio models, and image or video generation. * Familiarity with DevOps and IaC tooling (GitHub Actions, Jenkins, Terraform, Helm, Kubernetes) and awareness of front-end stacks (React, Angular, TypeScript, GraphQL) used in copilot interfaces. * Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education. * This position may require relocation and/or travel to work/project location. * All applicants authorized to work in the United States are encouraged to apply., Amazon Web Services (AWS), Analysis Skills, Application Programming Interface (API), Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Automation, Business Skills, Cloud Computing, Communication Skills, Consulting, Continuous Improvement, Data Quality, Data Science, Deep Learning, DevOps, Documentation Models, Ecosystems, Establish Priorities, GitHub, GraphQL, Healthcare Reimbursement, Jenkins, Kernel Programming, Leading Edge Technology, Life Insurance, Machine Learning, Machine Tool, Medical Conditions, Metrics, Microsoft Windows Azure, Middleware, Model Validation, Modeling Languages, Open Source, Performance Modeling, Performance Tuning/Optimization, Power Amplifier, Predictive Modeling, Problem Solving Skills, Process Improvement, Production Systems, Python Programming/Scripting Language, Quality Metrics, R Programming Language, React.js, Relational Databases (RDBMS), Reporting Skills, Requirements Management, Safety Compliance, Scripting (Scripting Languages), Statistical Algorithms, Statistical Analysis System (SAS), Statistical Modeling, Systems Administration/Management, Team Building, Test Plan/Schedule, Test Tools, User Interface/Experience (UI/UX), Validation Testing, Vision Plan, Willing to Travel ## Description significant impact, Infosys Topaz is the perfect place for you to grow and excel.In the assigned Job Role of Data Science Consultant 1, your Area Of Responsibility will be as below: * Participate in data extraction, transformation, and preparation. * Resolve common data issues and ensure quality for model development. * Participate in developing models using statistical or machine learning techniques and collaborate with technology teams to operationalize them into analytics tools or scripts. * Participate in model testing and validation, selecting the best-performing algorithms based on statistical and business metrics. * Participate in the development of advanced analytics and machine learning or deep learning models including LLMs using predefined processes and tools like SAS and R/ Python. * Participate in defining analytics problems; execute visualization, analysis, and predictive modeling with senior support. * Identify data sources and extract from RDBMS and develop UI/UX for client usage. * Participate in model performance, while making minor adjustments, and escalate risks or compliance concerns and generate reports on deviations or schedule slippages. * Proactively participate in detailed documentation of model development, testing, and deployment activities for reproducibility. * Work closely with business and technology teams to translate requirements into actionable models, while communicating results effectively. * Apply predefined quality measurement frameworks, if any, to individual project tasks. * Participate in deploying analytics tools in test and production environment, while ensuring they meet operational requirements.