Mogi I/O : OTT/Podcast/Short Video Apps for you
Lead Applied AI Engineer – Large Language Models & AWS MLOps
Mogi I/O : OTT/Podcast/Short Video Apps for you, Dallas, Texas, United States, 75215
Work Type:
Full Time Experience Required:
8 years software engineering with AI/ML focus, 3 years technical leadership
About The Company
Our client is a leading technology consulting firm specializing in intelligent systems and AI-powered solutions. They work with enterprise clients to architect and deploy cutting-edge AI applications, from generative AI copilots to complex machine learning pipelines, helping organizations transform their operations through advanced artificial intelligence.
Job Overview
Join as a Senior AI Engineer leading the architecture and implementation of advanced AI and machine learning systems that solve complex business problems. You’ll work at the forefront of generative AI, building LLM-based applications, AI copilots, and intelligent workflows while mentoring engineering teams and driving AI strategy for enterprise clients.
Key Responsibilities
Architect and implement advanced AI/ML systems solving complex business challenges
Lead design and deployment of LLM-based applications using LangChain, LlamaIndex, and vector databases
Develop end-to-end ML pipelines from data acquisition and model training to deployment and monitoring
Design and build AI copilots, agents, and generative workflows integrated into modern software ecosystems
Apply deep expertise in NLP, computer vision, or predictive modeling for intelligent, real-time systems
Evaluate and fine-tune foundation models for custom enterprise use cases
Collaborate with cross-functional teams (product, design, engineering) to define intelligent experiences
Implement RAG, semantic search, and multi-modal reasoning technologies
Contribute to internal AI frameworks and accelerators to speed solution delivery
Mentor engineers on AI architecture, model lifecycle best practices, and ethical ML use
Lead client-facing discussions on AI strategy and technical implementations
Must-Have Requirements
8 years software engineering experience with strong AI/ML and intelligent systems focus
3 years technical leadership role building and deploying ML systems in production
Deep Python expertise and modern AI/ML libraries (PyTorch, TensorFlow, Hugging Face Transformers)
LLM experience with OpenAI, Anthropic, Cohere, open source LLMs, and prompt engineering
Vector database familiarity (Pinecone, Weaviate, FAISS) and scalable ML infrastructure
AI system design knowledge including data engineering for ML, model evaluation, MLOps practices
Full-stack AI integration experience in cloud-native environments, specifically AWS
Strong communication skills and consulting mindset for client-facing AI strategy discussions
Innovation passion for experimentation and shaping the future of applied AI
Nice-to-Have Skills
Advanced degree in Computer Science, AI/ML, or related technical field
Multi-modal AI experience combining vision, language, and reasoning capabilities
Enterprise AI deployment experience with scalability, security, and compliance requirements
Research background with publications in AI/ML conferences or journals
Domain expertise in specific verticals (healthcare, finance, retail, etc.)
Open source contributions to AI/ML frameworks or communities
Work Environment & Culture
Remote-first consulting environment with collaborative, innovation-focused culture
Cutting-edge technology exposure with access to latest AI tools and platforms
Client variety across industries and use cases, from startups to Fortune 500
Professional development opportunities and conference attendance support
Technical leadership path with mentoring and architectural decision-making responsibilities
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Full Time Experience Required:
8 years software engineering with AI/ML focus, 3 years technical leadership
About The Company
Our client is a leading technology consulting firm specializing in intelligent systems and AI-powered solutions. They work with enterprise clients to architect and deploy cutting-edge AI applications, from generative AI copilots to complex machine learning pipelines, helping organizations transform their operations through advanced artificial intelligence.
Job Overview
Join as a Senior AI Engineer leading the architecture and implementation of advanced AI and machine learning systems that solve complex business problems. You’ll work at the forefront of generative AI, building LLM-based applications, AI copilots, and intelligent workflows while mentoring engineering teams and driving AI strategy for enterprise clients.
Key Responsibilities
Architect and implement advanced AI/ML systems solving complex business challenges
Lead design and deployment of LLM-based applications using LangChain, LlamaIndex, and vector databases
Develop end-to-end ML pipelines from data acquisition and model training to deployment and monitoring
Design and build AI copilots, agents, and generative workflows integrated into modern software ecosystems
Apply deep expertise in NLP, computer vision, or predictive modeling for intelligent, real-time systems
Evaluate and fine-tune foundation models for custom enterprise use cases
Collaborate with cross-functional teams (product, design, engineering) to define intelligent experiences
Implement RAG, semantic search, and multi-modal reasoning technologies
Contribute to internal AI frameworks and accelerators to speed solution delivery
Mentor engineers on AI architecture, model lifecycle best practices, and ethical ML use
Lead client-facing discussions on AI strategy and technical implementations
Must-Have Requirements
8 years software engineering experience with strong AI/ML and intelligent systems focus
3 years technical leadership role building and deploying ML systems in production
Deep Python expertise and modern AI/ML libraries (PyTorch, TensorFlow, Hugging Face Transformers)
LLM experience with OpenAI, Anthropic, Cohere, open source LLMs, and prompt engineering
Vector database familiarity (Pinecone, Weaviate, FAISS) and scalable ML infrastructure
AI system design knowledge including data engineering for ML, model evaluation, MLOps practices
Full-stack AI integration experience in cloud-native environments, specifically AWS
Strong communication skills and consulting mindset for client-facing AI strategy discussions
Innovation passion for experimentation and shaping the future of applied AI
Nice-to-Have Skills
Advanced degree in Computer Science, AI/ML, or related technical field
Multi-modal AI experience combining vision, language, and reasoning capabilities
Enterprise AI deployment experience with scalability, security, and compliance requirements
Research background with publications in AI/ML conferences or journals
Domain expertise in specific verticals (healthcare, finance, retail, etc.)
Open source contributions to AI/ML frameworks or communities
Work Environment & Culture
Remote-first consulting environment with collaborative, innovation-focused culture
Cutting-edge technology exposure with access to latest AI tools and platforms
Client variety across industries and use cases, from startups to Fortune 500
Professional development opportunities and conference attendance support
Technical leadership path with mentoring and architectural decision-making responsibilities
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