Senior AI Systems Engineer (Agentic, LLM)

Salary: $104,000 - 124,800 per year Requirements:

• We need at least 5 years of software development experience in one or more languages such as Python, C/C++, Go, or Java, with strong hands-on experience building and supporting large-scale Python applications preferred.
• We need at least 3 years of experience designing, architecting, testing, and launching production ML systems, including model deployment and serving, evaluation and monitoring, data processing pipelines, and model fine-tuning workflows.
• We need practical experience with large language models, including API integration, prompt engineering, fine-tuning or adaptation, and building applications with RAG and tool-using agents such as vector retrieval, function calling, and secure tool execution.
• We need a solid understanding of different commercial and open-source LLMs and their capabilities, such as OpenAI, Gemini, Llama, Qwen, and Claude.
• We need a strong grasp of applied statistics, core ML concepts, algorithms, and data structures to deliver efficient and dependable solutions.
• We need strong analytical problem-solving skills, ownership, urgency, and the ability to explain complex ideas clearly while collaborating effectively across global teams with a focus on measurable business impact.
• Preferred: We value experience building and operating cloud infrastructure, ideally on AWS, including containerized services like ECS and EKS, serverless services like Lambda, data services such as S3, DynamoDB, and Redshift, orchestration with Step Functions, model serving with SageMaker, and infrastructure as code using Terraform or CloudFormation.

• We design and implement agentic AI systems, including tool-calling agents that combine retrieval, structured reasoning, and secure action execution in line with MCP protocol, while building strong guardrails for safety, compliance, and least-privilege access.
• We productionize LLMs by creating evaluation frameworks for open-source and foundational models and by implementing retrieval pipelines, prompt synthesis, response validation, and self-correction loops for production operations.
• We integrate agents with observability, incident management, and deployment platforms so we can automate diagnostics, runbook execution, remediation, and post-incident summaries with full traceability.
• We partner directly with production engineers and application teams to turn operational pain points into agentic AI roadmaps, define objective functions tied to reliability, risk reduction, and cost, and deliver auditable outcomes aligned to the business.
• We embed validator models, adversarial prompts, and policy controls into the stack, enforce deterministic fallbacks, circuit breakers, and rollback strategies, and run continuous evaluations for usefulness, correctness, and risk.
• We optimize performance and cost through prompt engineering, context management, caching, model routing, and distillation, while using batching, streaming, and parallel tool calls to meet strict service-level objectives under real-world load.
• We build a RAG pipeline by curating domain knowledge, establishing data-quality validation, and creating feedback loops and milestone tracking to keep knowledge fresh.
• We lead design reviews, promote rigorous experimentation, uphold high-quality engineering standards, and mentor peers on agent architectures, evaluation methods, and safe deployment practices.

• Agentic AI
• AI
• API
• AWS
• Lambda
• Redshift
• Cloud
• Fine-tuning
• Incident Management
• Java
• MCP
• Model Serving
• Python
• RAG
• Serverless
• Terraform

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We are NTT DATA, a $30 billion global innovator in business and technology services, supporting 75% of the Fortune Global 100 with consulting, data and artificial intelligence, industry solutions, and application, infrastructure, and connectivity services. We are a Global Top Employer with diverse experts in more than 50 countries and a strong ecosystem of established and start-up partners. This role is with our client and is based in New York, Dallas, or remote within the United States. The starting hourly range for this remote position is $50 to $60, with actual pay depending on location, experience, technical skills, and other qualifications, and the role may also qualify for incentive compensation based on performance. We are an equal opportunity employer committed to accessibility and inclusive hiring.

last updated 33 week of 2026