Title: AI Engineer

Location: Dallas, TX (Day 1 Onsite)

Role Overview

We 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 technical skills for Agentic AI in 2026 involve building autonomous, multi-step workflows using Python, LLM orchestration frameworks (LangChain, AutoGen), and API integration. Core competencies include prompt engineering, agentic RAG for data retrieval, planning/reasoning capabilities, and developing robust memory management

Key Technical Skills & Usage Examples

Programming (Python): Essential for writing logic, connecting APIs, and building end-to-end workflows.
Frameworks (LangChain, AutoGen, CrewAI): Used for developing autonomous agent teams and multi-agent orchestration.
Prompt Engineering & Instruction Design: Creating structured prompts to improve task success rates by up to 35%.
Planning & Reasoning: Designing agents that break down complex goals into actionable sub-tasks.
Tool Use & API Orchestration: Connecting AI models to external tools (databases, browsers, calculators) to act upon data, increasing success by 46%.
Vector Databases & RAG: Implementing retrieval-augmented generation for memory and knowledge management.
Evaluation & Testing: Testing agent reliability, accuracy, and monitoring for hallucination

Key Responsibilities

Design, develop, and maintain scalable AI/ML applications, with a strong focus on Python-based systems
Architect, build, and deploy production ML systems including model serving, evaluation, monitoring, and data pipelines
Develop and implement solutions using Large Language Models (LLMs), including prompt engineering, fine-tuning, and RAG-based applications
Integrate LLM APIs and build intelligent applications using vector databases, tool-based agents, and function calling
Collaborate with cross-functional teams to translate business requirements into scalable AI solutions
Ensure performance, scalability, and reliability of deployed AI systems
Continuously evaluate and adopt emerging AI/ML technologies and best practices

Required Skills & Qualifications

5+ years of software development experience in one or more languages: Python (preferred), C/C++, Go, or Java
3+ years of experience designing, building, and deploying production ML systems
Hands-on experience with LLMs including API integration, prompt engineering, fine-tuning, and RAG architectures
Familiarity with leading LLMs such as OpenAI, Gemini, Llama, Qwen, and Claude
Strong understanding of machine learning concepts, applied statistics, algorithms, and data structures
Experience building data pipelines and handling large-scale datasets
Strong problem-solving skills, ownership mindset, and ability to work in a fast-paced environment
Excellent communication skills with the ability to explain complex concepts clearly

Preferred Qualifications

Experience 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