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# Python AI/ML Engineer (ONLY W2)

- **Company:** TekFortune INC
- **Location:** Irving, TX, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** LangGraph Framework, Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Databases, Continuous Integration, Graph Database, Python (Programming Language), Machine Learning, Tensorflow, Standard Sql, Search Technologies, Pinecone, Google Cloud, Pytorch, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, IT Architecture, Deep Learning, Generative AI, Agentic-AI, Git, Fastapi, Containerization, Scikit Learn, Kubernetes, Xgboost, Machine Learning Operations, FAISS, Graph RAG, Restful APIs, OpenSearch, Docker, Agent2Agent Protocol
- **Published:** October 15, 2026
- **Apply:** https://www.dice.com/job-detail/1ac918d7-dc97-4d4e-9907-c845a7fa508c

## About the Role

Strong Python, LLM and Prompt engineering expertise with Java, Core Technical Skills

 * Programming: Python, SQL

 * Machine Learning: Scikit-learn, XGBoost/LightGBM

 * Deep Learning: PyTorch / TensorFlow

 * GenAI: LLMs, Prompt Engineering, Embeddings, RAG

 * Agentic AI: LangGraph, LangChain or equivalent frameworks

 * Vector Search: OpenSearch, FAISS, Pinecone or equivalent

 * MLOps: MLflow, Docker, CI/CD, model deployment & monitoring

 * Cloud: AWS / Azure / Google Cloud Platform

 * APIs & Engineering: REST APIs, FastAPI, Git, containerization

Good to Have

 * MCP and A2A protocols

 * Multi-agent systems

 * LLM and RAG evaluation

 * AI observability and guardrails

 * Kubernetes

 * Knowledge Graph / Graph RAG

 * Experience with enterprise-scale AI applications, * The ideal candidate should be a hands-on AI engineer who can take an AI use case from problem definition through development, deployment, and production monitoring.
 * Strong problem-solving, communication, system-design, and mentoring skills are expected.

## Description

* We are looking for a Senior AI/ML Engineer with strong hands-on experience across Machine Learning, Deep Learning, MLOps, Generative AI, and Agentic AI.

 * The candidate will be responsible for designing, developing, deploying, and scaling AI solutions for enterprise use cases.

Key Responsibilities

 * Design and develop end-to-end Machine Learning and Deep Learning solutions.

 * Build and productionize ML models using appropriate algorithms and frameworks.

 * Develop and manage MLOps pipelines covering model training, deployment, monitoring, and lifecycle management.

 * Build Generative AI applications using LLMs, prompt engineering, embeddings, RAG, and vector databases.

 * Design and implement Agentic AI solutions, including AI agents, tool calling, multi-agent workflows, and orchestration.

 * Integrate AI solutions with enterprise APIs, databases, applications, and knowledge sources.

 * Deploy scalable AI solutions on AWS, Azure, or Google Cloud Platform.

 * Implement AI application monitoring, evaluation, observability, security, and responsible AI practices.

 * Collaborate with product, engineering, data, and business teams to translate business problems into AI solutions.

 * Mentor junior engineers and contribute to AI architecture and technology strategy.