Sr AI Engineer

Lead the architecture and optimization of agentic AI systems for customer service automation.

Responsibilities

• Design, develop, and deploy scalable, production-grade Generative AI applications, LLM-powered solutions, and agentic AI systems for enterprise operations and customer service automation
• Architect and implement AI agents and multi-agent orchestration workflows using LangGraph, LangChain, or equivalent technologies
• Develop Retrieval-Augmented Generation (RAG) solutions using embeddings, vector databases, semantic search, and enterprise knowledge sources
• Build and integrate RESTful APIs, Model Context Protocol (MCP) connectors, and enterprise data services for secure AI interactions with internal and external systems
• Optimize AI performance through prompt engineering, model selection, retrieval optimization, fine-tuning, and efficient inference strategies for customer service outcomes
• Design and implement AI evaluation frameworks to measure accuracy, hallucination rates, reliability, latency, throughput, and cost efficiency
• Develop cloud-native AI solutions on Azure, AWS, or equivalent platforms using containerization and scalable architectures with automated deployment
• Implement security, governance, and responsible AI practices including authentication, authorization, data privacy, and prompt injection protection aligned to enterprise compliance requirements
• Establish observability for AI applications and agentic workflows through logging, monitoring, and production troubleshooting
• Collaborate with cross-functional engineering, architecture, product, cybersecurity, and business teams to integrate AI-driven enhancements into production systems
• Conduct technical design reviews, participate in code reviews, mentor engineers, and contribute to reusable engineering standards and best practices
• Research and evaluate emerging AI technologies and open-source frameworks to support innovation and continuous improvement for customer service automation
• Perform other duties and projects as assigned by business management

Requirements

• 5+ years of related work experience (or advanced degree with 3 years)
• Python proficiency plus strong software engineering principles and object-oriented programming
• Experience designing, developing, securing, and integrating RESTful APIs using FastAPI or equivalent
• Hands-on experience building LLM applications including prompt engineering, structured outputs, function calling, and tool integration
• Experience developing agentic AI systems, tool-calling workflows, and orchestration solutions using LangGraph, LangChain, or similar frameworks
• Knowledge of embeddings, vector databases, semantic retrieval, document processing, and data integration
• Experience developing and deploying applications on Azure, AWS, or Google Cloud
• Proficiency with Git, CI/CD pipelines, automated testing, and production software development practices
• Ability to design scalable, secure, reliable, and maintainable distributed applications
• Strong analytical skills working with structured and unstructured data
• Understanding of AI evaluation including performance benchmarking, accuracy measurement, and AI quality assurance
• Strong communication, problem-solving, and cross-functional collaboration skills

Required Education & Experience

• Required: Bachelor’s Degree plus 5 years of related work experience
• Alternative: Advanced degree plus 3 years of related work experience
• 4+ yrs developing and optimizing AI models for customer service automation using prompt engineering and fine-tuning
• 4+ yrs architecting and deploying sophisticated agentic AI systems to improve reasoning and interaction in complex workflows
• 4+ yrs collaborating with cross-functional teams to integrate AI-driven enhancements into production systems
• Acceptable areas of study: Computer Science, Artificial Intelligence, or Related Field

Preferred

• Experience with Model Context Protocol (MCP) and enterprise AI tool integrations
• Experience with Docker, Kubernetes, and cloud-native deployment tooling for AI workloads
• Certified Analytics Professional (CAP)
• NVIDIA Deep Learning AI Certification
• Master’s/Advanced Degree in Computer Science, Artificial Intelligence, or Data Science

Certifications

• Preferred: Certified Analytics Professional (CAP)
• Preferred: NVIDIA Deep Learning AI Certification
• Preferred: Certified Data Scientist (CDS)

Technologies

• Python
• RESTful APIs
• FastAPI
• LLMs
• LangGraph
• LangChain
• Model Context Protocol (MCP)
• RAG
• Embeddings
• Vector databases
• Semantic search
• Azure
• AWS
• Google Cloud
• Containerization
• CI/CD pipelines
• Git
• Authentication
• Authorization
• Prompt injection protection

Compensation

• National Base Pay Range: USD 133,100 - 240,100 per year
• Total Target Cash Earnings Opportunity: USD 153,065 - 276,115

Location & Work Type

• Frisco, TX (onsite)
• Travel: No
• DOT regulated: No
• Safety sensitive position: No

Other Qualifications

• At least 18 years of age
• Legally authorized to work in the United States

Benefits

• Medical, dental and vision insurance
• Flexible spending account
• 401(k)
• Employee stock grants
• Employee stock purchase plan
• Paid time off and up to 12 paid holidays
• Paid parental and family leave
• Family building benefits
• Back-up care
• Enhanced family support
• Childcare subsidy
• Tuition assistance
• College coaching
• Short- and long-term disability
• Voluntary AD&D coverage
• Voluntary accident coverage
• Voluntary life insurance
• Voluntary disability insurance
• Voluntary long-term care insurance
• Mobile service & home internet discounts (eligible employees)
• Pet insurance (eligible employees)
• Access to commuter and transit programs (eligible employees)
• Annual bonus or periodic sales incentive or bonus (eligible regular, non-temporary roles)
• Year-end bonus for corporate employees (eligible)