Senior AI Engineer GenAI / Agentic AI / Machine Learning

Job Title: Senior AI Engineer – GenAI / Agentic AI / Machine Learning

Location: Sunrise, FL / Phoenix, AZ
Employment Type: Full Time
Job Type: Permanent / Direct Hire

Job Summary

We are seeking a highly skilled Senior AI Engineer with strong hands-on software development and coding expertise across Machine Learning, Generative AI, Agentic AI, LLMs, RAG, and multimodal AI.

The ideal candidate must be a strong hands-on coder with advanced Python programming skills and proven experience designing, developing, deploying, and optimizing production-grade AI/ML solutions.

This role is best suited for an experienced AI/ML Engineer who can independently write production-quality code, build ML pipelines, develop LLM-powered applications, implement AI agents, and take AI solutions from development through deployment and monitoring.

Candidate Profile

Strong preference for senior candidates with hands-on coding experience.

Candidates should demonstrate:

• Strong production-level Python coding skills.

• Strong understanding of Object-Oriented Programming (OOP).

• Ability to design and implement complex AI/ML solutions independently.

• Hands-on experience building and deploying Machine Learning and Generative AI applications.

• Experience developing LLM-powered applications, RAG pipelines, and AI agents.

• Experience with LangChain, LangGraph, LlamaIndex, vector databases, and LLM APIs.

• Ability to work across the complete AI lifecycle from data ingestion → model development → evaluation → deployment → monitoring.

• Strong software engineering fundamentals, including data structures, algorithms, design patterns, testing, debugging, and exception handling.

Required Technical Skills

<>Python & Software Engineering

Strong hands-on experience with:

• Python

• Object-Oriented Programming (OOP)

• Functions and Modules

• Iterators and Generators

• Exception Handling

• Decorators

• Type Hints / Typing

• Data Classes

• Data Structures & Algorithms

• Design Patterns

• Unit Testing

• Debugging

• Clean Code

• Software Development Best Practices

• API Development

Machine Learning

• NumPy

• Pandas

• Scikit-learn

• XGBoost

• LightGBM

• PyTorch

• TensorFlow

• MLflow

• Matplotlib

• Feature Engineering

• Model Training

• Model Evaluation

• Model Optimization

• Hyperparameter Tuning

• Model Deployment

• Model Monitoring

Generative AI & LLM

• Generative AI / GenAI

• Large Language Models (LLMs)

• Prompt Engineering

• LLM Application Development

• LLM APIs

• Retrieval-Augmented Generation (RAG)

• Embeddings

• Vector Search

• Vector Databases

• Context Management

• AI Application Architecture

• LLM Evaluation

• Model Optimization

Agentic AI

• Agentic AI

• AI Agents

• Autonomous AI Agents

• Agent Orchestration

• Multi-Agent Systems

• LangGraph

• LangChain

• LlamaIndex

• Agent Workflows

• Tool Calling / Function Calling

• Tool Integration

• Agent Memory

• Context Management

LLM / AI Platforms

Hands-on experience with one or more:

• OpenAI APIs

• Anthropic APIs / Claude

• Google Gemini APIs

• Azure OpenAI

• AWS Bedrock

Vector Databases

Experience with one or more:

• FAISS

• Pinecone

• Weaviate

• Milvus

• Chroma

• OpenSearch / Vector Search

Multimodal AI

• Multimodal AI application development

• Text-based AI

• Image understanding and generation

• Audio processing

• Video processing

• Vision-Language Models (VLMs)

• Multimodal LLMs

• Multimodal RAG

Key Responsibilities

• Design, develop, test, deploy, and maintain scalable AI and Machine Learning solutions.

• Write high-quality, production-ready Python code for AI/ML applications.

• Build and optimize end-to-end machine learning pipelines from data ingestion through model deployment and monitoring.

• Develop advanced Generative AI applications using LLMs, RAG, embeddings, vector databases, and AI agents.

• Design and implement Agentic AI systems using LangGraph, LangChain, LlamaIndex, and related frameworks.

• Develop reusable AI/ML components, services, APIs, and application frameworks.

• Build and optimize RAG pipelines, including document ingestion, chunking, embedding, retrieval, ranking, and context generation.

• Integrate AI applications with OpenAI, Anthropic, Gemini, AWS, and other enterprise AI platforms.

• Design and implement multimodal AI solutions supporting text, image, audio, and video.

• Develop AI agents capable of tool calling, API integration, reasoning workflows, and task automation.

• Evaluate AI models and applications for accuracy, latency, scalability, reliability, security, and cost.

• Implement model evaluation, monitoring, observability, and performance optimization.

• Apply AI engineering best practices for security, governance, responsible AI, and production readiness.

• Evaluate emerging AI technologies, frameworks, models, and tools.

• Collaborate with Product Managers, Business Stakeholders, Data Engineers, Cloud Engineers, and Solution Architects.

• Translate business requirements into scalable technical AI solutions.

• Provide technical leadership and mentorship to other AI/ML engineers.

• Conduct code reviews, architecture reviews, and technical design discussions.

• Communicate technical concepts, solution architecture, project progress, and business impact to technical and non-technical stakeholders.

AI/ML Engineering Lifecycle

The ideal candidate should have hands-on experience across:

Data Ingestion → Data Preparation → Feature Engineering → Model Development → Model Training → Model Evaluation → LLM/RAG Development → AI Agent Development → API Integration → Deployment → Monitoring → Optimization

Preferred Skills

• Experience deploying AI applications in AWS, Azure, or Google Cloud.

• Experience with Docker and Kubernetes.

• Experience developing REST APIs and microservices.

• Experience with FastAPI, Flask, or similar Python frameworks.

• Experience with CI/CD and DevOps practices.

• Experience with MLOps and MLflow.

• Experience with cloud-native AI/ML architectures.

• Experience with AI evaluation frameworks and LLM observability.

• Experience with MCP (Model Context Protocol) and tool integration.

• Experience with multi-agent orchestration and agent-to-agent workflows.

• Experience with production-scale AI systems and enterprise applications.

Senior-Level Expectations

• Strong ability to independently solve complex AI/ML engineering problems.

• Strong coding and software engineering fundamentals.

• Ability to design scalable AI architectures and convert designs into working production code.

• Ability to perform technical research and evaluate emerging AI technologies.

• Ability to mentor engineers and establish AI engineering best practices.

• Strong understanding of production reliability, scalability, security, and maintainability.

• Ability to communicate effectively with engineering teams, architects, product teams, and business stakeholders.

Core Dice Search Keywords

Senior AI Engineer, AI Engineer, Senior AI/ML Engineer, Machine Learning Engineer, ML Engineer, Generative AI Engineer, GenAI Engineer, AI Developer, LLM Engineer, AI Software Engineer, Applied AI Engineer, Agentic AI Engineer, AI Agent Engineer, Python Developer, Python AI Engineer, Machine Learning, Artificial Intelligence, Generative AI, GenAI, Agentic AI, AI Agents, LLM, Large Language Models, RAG, Retrieval Augmented Generation, Prompt Engineering, LangChain, LangGraph, LlamaIndex, OpenAI, OpenAI API, Anthropic, Claude, Gemini, AWS Bedrock, Azure OpenAI, Vector Database, Vector DB, FAISS, Pinecone, Weaviate, Milvus, Chroma, Embeddings, Semantic Search, Multimodal AI, Multimodal LLM, Vision Language Models, PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM, NumPy, Pandas, MLflow, Python, OOP, Object Oriented Programming, Data Structures, Algorithms, Design Patterns, REST API, FastAPI, Microservices, Docker, Kubernetes, MLOps, CI/CD, AI Architecture, LLM Evaluation, AI Agents, Agent Orchestration, Tool Calling, Function Calling, MCP, Model Context Protocol.

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical field preferred.

Location

Sunrise, FL / Phoenix, AZ

Employment Type

Full Time / Permanent