Service Delivery Center, AI & Data, AI Developer - Senior

13 days ago

San Antonio, TX, USASenior

H1B sponsor

Base Salary

$66k - $134k/yr

Responsibilities

Develop, test, deploy, and support production-grade AI/ML, generative AI, and intelligent automation solutions.
Build and integrate LLM, RAG, and agentic components into enterprise applications, platforms, and broader solutions.
Translate user requirements into technical designs, APIs, workflows, and supportable implementation patterns.
Debug, troubleshoot, and remediate issues across development, integration, retrieval, orchestration, generation, and production support layers.
Design and implement multi-agent orchestration, tool use, memory, prompt engineering, embedding, vector search, and semantic retrieval capabilities.
Apply Python software engineering practices, testing patterns, data quality validation, containerization, cloud deployment, and operationalization practices.
Participate in design reviews, estimation, documentation, status communication, risk identification, and trade-off analysis.
Collaborate with engineering, product, data, architecture, development, and project leadership teams.
Build model observability pipelines for agent tracing, output degradation detection, and behavioral drift monitoring.

Bachelor's or master's degree.
At least 2 years of related work experience, including meaningful applied engineering experience in AI/ML engineering roles.
Hands-on proficiency in Python and experience writing clean, modular, production-quality code for LLM pipelines and agentic applications.
Experience designing, building, and maintaining production-grade LLM applications and retrieval-augmented systems.
Experience with structured and unstructured data preparation, curation, quality validation, RESTful and event-driven APIs, and asynchronous workflows.
Practical understanding of containerization, orchestration, cloud deployment, software testing, data observability, and AI-system operationalization.
Ability to explain complex AI system behavior and trade-offs to technical and non-technical stakeholders, including risk and compliance considerations.
Preferred familiarity with model observability, LLM fine-tuning, responsible AI, AI data pipelines, cloud AI platforms, AI-assisted engineering tools, and traditional machine learning and deep learning fundamentals.
Preferred experience with supervised and unsupervised learning, feature engineering, model evaluation, neural network architectures, and training trade-offs.
Strong ownership, accountability, adaptability, collaboration, and communication skills.

Base salary range is $65,500 to $134,000 for US geographic locations, with a separate range of $78,600 to $152,100 for New York City Metro Area, Washington State, and California excluding Sacramento.
Medical and dental coverage, pension, and 401(k) plans are offered.
Benefits include paid time off, EY-paid holidays, winter and summer breaks, personal and family care leave, and other leaves of absence.
The role follows a flexible hybrid model, with most external client-serving employees expected to work in person 40–60% of the time during an engagement, project, or year.
Flexible vacation policy is available.
Applications are accepted on an ongoing basis, and reasonable accommodations are available.

10,000+ employees