AI ENGINEER

Job Title: AI EngineerLocation: Dallas, TX Duration: Long term contract IDEAL PROFILE:Python-first AI Engineer who builds production ML + Agentic AI systems at enterprise scale using AWS.1. Strong Engineering Foundation (Critical)- Python is primary language- Builds scalable backend services/APIs- Shows performance optimization (latency, throughput)2. Agentic AI (Top Filter)- Hands-on with LangChain / AutoGen / CrewAI- RAG pipelines with vector DBs- Real use case with impact metrics3. AWS Cloud Depth- SageMaker, EKS/ECS, Lambda, S3- Real deployment examples4. ML + Statistics Foundations- Evaluation metrics (precision, recall, F1, AUC)- ML concepts & algorithms5. Production ML Systems- End-to-end lifecycle: training, deployment, monitoring- Model serving & monitoring6. Analytical Problem Solving- Problem → Solution → Impact- Measurable results7. Enterprise Platform Experience- Platform-level systems used across teams- High-scale, distributed systemsRole OverviewWe are seeking a highly skilled AI Engineer to design, develop, and deploy scalable machine learning and AI-driven solutions. The ideal candidate will have strong experience in building production-grade ML systems, working with Large Language Models (LLMs), and delivering high-impact applications in a cloud-based environment.Key ResponsibilitiesDesign, develop, and maintain scalable AI/ML applications, with a strong focus on Python-based systemsArchitect, build, and deploy production ML systems including model serving, evaluation, monitoring, and data pipelinesDevelop and implement solutions using Large Language Models (LLMs), including prompt engineering, fine-tuning, and RAG-based applicationsIntegrate LLM APIs and build intelligent applications using vector databases, tool-based agents, and function callingCollaborate with cross-functional teams to translate business requirements into scalable AI solutionsEnsure performance, scalability, and reliability of deployed AI systemsContinuously evaluate and adopt emerging AI/ML technologies and best practicesRequired Skills & Qualifications5+ years of software development experience in one or more languages: Python (preferred), C/C++, Go, or Java3+ years of experience designing, building, and deploying production ML systemsHands-on experience with LLMs including API integration, prompt engineering, fine-tuning, and RAG architecturesFamiliarity with leading LLMs such as OpenAI, Gemini, Llama, Qwen, and ClaudeStrong understanding of machine learning concepts, applied statistics, algorithms, and data structuresExperience building data pipelines and handling large-scale datasetsStrong problem-solving skills, ownership mindset, and ability to work in a fast-paced environmentExcellent communication skills with the ability to explain complex concepts clearlyPreferred QualificationsExperience working with AWS cloud services (ECS/EKS, Lambda, S3, DynamoDB, Redshift, SageMaker)Knowledge of containerization and orchestration (Docker, Kubernetes)Experience with workflow orchestration (Step Functions)Familiarity with Infrastructure as Code tools such as Terraform or CloudFormation