2 months ago
San Antonio, TX, USAMid Level
Responsibilities
- Design, develop, test, and deploy AI-powered applications and agentic AI solutions for operational and business objectives.
- Build and optimize AI workflows using foundation models, open-source LLMs, internally trained models, prompt engineering, RAG, vector databases, and agent-to-agent communication.
- Develop and maintain AI agents, APIs, and services for scalable and secure enterprise AI operations.
- Deploy and support AI and machine learning models in production, ensuring reliability, scalability, performance, and ongoing optimization.
- Develop data pipelines supporting model training, inference, and AI application performance.
- Partner with business and technology stakeholders to evaluate use cases and translate requirements into AI solutions.
- Ensure solutions follow Responsible AI principles, security standards, governance requirements, and regulatory expectations.
- Contribute to AI architecture evolution and document solution architectures, workflows, models, and technical processes.
- Evaluate emerging AI technologies, models, and frameworks to identify innovation opportunities.
Requirements
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
- At least three years of professional experience developing AI, machine learning, or generative AI solutions.
- Hands-on experience developing and deploying solutions with Python.
- Experience building agentic AI systems, AI-powered workflows, APIs, and enterprise AI integrations.
- Working knowledge of LLMs, foundation models, prompt engineering, generative AI, vector databases, RAG, fine-tuning, and model deployment.
- Experience using pre-trained and custom-trained AI models and working in AWS cloud environments with AWS AI services.
- Knowledge of data pipelines supporting AI and machine learning workflows.
- Experience in regulated environments with security, governance, and Responsible AI principles.
- Strong problem-solving, communication, and cross-functional collaboration skills.
- Preferred: AWS Certified Machine Learning Engineer – Associate certification, AWS Certified Generative AI Developer – Professional certification, open-source LLM training or hosting experience, AWS Bedrock and Bedrock AgentCore experience, LangChain, LangGraph, Strands, MCP, agent-to-agent protocols, C# development, production AI support, and MLOps exposure.
Benefits
- Competitive overall compensation package.
- Work/life balance, employee engagement activities, recognition awards, and Years of Service awards.
- Career enhancement and growth opportunities, Leadership Academy, and Mentor Program.
- Continuing education and career certifications.
- Variety of healthcare coverage options.
- Traditional and Roth 401(k) retirement plans.
- Lucrative Wellness Program.
- Benefits are subject to employee eligibility; the role includes pre-employment drug testing and is at a substance-free workplace that does not hire tobacco users as allowed by law.