AI Foundational Model Engineer

NTT DATA North America; Jersey City (NJ); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Medical

Dental

Vision insurance

401k with company match

Paid time off

Life and AD&D insurance

Short term disability

Long term disability

Employee assistance

Job summary

NTT DATA North America seeks an AI Foundation Model Engineer to design, build, deploy and optimize enterprise-grade AI systems powered by foundation models and LLMs in Jersey City, NJ. You will work on AIRP on AWS, with a cloud-agnostic blueprint, contributing to end-to-end LLMOps and secure AI service delivery.

Responsibilities include building knowledge assistants, RAG pipelines, and model-serving integration while collaborating with Terraform/IaC and CI/CD teams.

Qualifications

• 7+ years in AI/ML engineering, platform engineering, software engineering, or applied machine learning.
• Hands-on experience with LLMs, transformers, embeddings, RAG, semantic search, and GenAI application patterns.
• Strong Python engineering skills with PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks.
• Experience deploying production AI services using APIs, containers, Kubernetes, CI/CD, cloud-native services, and monitoring platforms.
• Practical exposure to AWS AI/cloud services or comparable cloud-native AI deployment experience, with ability to ramp quickly on AWS-hosted AIRP patterns.
• Working knowledge of Terraform/IaC, DevOps pipelines, release management, model evaluation, inference optimization, and secure data handling.

Responsibilities

• Design and implement LLM-powered applications such as knowledge assistants, document intelligence solutions, workflow agents, summarization tools, and decision-support systems.
• Build RAG pipelines using embeddings, chunking strategies, vector databases, semantic retrieval, reranking, response grounding, and citation patterns.
• Integrate AI capabilities with AWS-hosted platform components, including model APIs, model gateways, data services, container platforms, and enterprise authentication patterns.
• Collaborate with cloud engineering teams on Terraform modules, IaC templates, environment promotion, CI/CD pipelines, release controls, and rollback procedures.
• Adapt and optimize models using LoRA, PEFT, instruction tuning, distillation, transfer learning, quantization, and domain adaptation techniques where appropriate.
• Optimize inference workloads for latency, throughput, token efficiency, cost, reliability, and user experience.
• Implement model and application observability, including prompt logs, retrieval quality, hallucination indicators, drift signals, feedback loops, cost telemetry, and service health.
• Embed security, privacy, Responsible AI, and model risk controls into AI application design and delivery.
• Create production documentation, runbooks, release notes, test evidence, and audit-ready implementation records.

Skills

LLMs

Transformers

Embeddings

RAG

Semantic search

GenAI

Tools

AWS

Terraform/IaC

CI/CD

Kubernetes

LangChain

Job description

Req ID: 382098
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization.

We are currently seeking a AI Foundational Model Engineer to join our team in Jersey City, New Jersey (US-NJ), United States (US).

AI Foundation Model Engineer

LLM / Agentic AI / Full-Stack AI Engineering

Role purpose

Design, build, deploy, and optimize enterprise-grade AI systems powered by foundation models, LLMs, retrieval-augmented generation, and agentic workflows. The role converts AI concepts into secure, scalable, observable, and supportable production systems on the enterprise AI-ready platform (AIRP), which is currently AWS-hosted while following a cloud-agnostic architecture blueprint.

Client-specific emphasis

• Hands-on AWS AI and cloud engineering is a major asset because AIRP currently runs on AWS.
• Candidates should be comfortable working with Terraform/IaC and CI/CD teams to move AI services and infrastructure through controlled deployment pipelines.
• Experience should map to business AI use cases such as KYC, credit underwriting, pitch book generation, Banker 360, Customer 360, deal library intelligence, financial crime quality, and sanctions screening.

Primary Ownership

• Production LLM applications, RAG pipelines, AI services, and model-serving integrations for AIRP.
• End-to-end LLMOps/MLOps lifecycle from experimentation to deployment, monitoring, evaluation, rollback, and continuous improvement.
• Reusable AI service components, APIs, prompts, retrieval logic, and observability patterns that can be federated across multiple business use cases.

Key Responsibilities

• Design and implement LLM-powered applications such as knowledge assistants, document intelligence solutions, workflow agents, summarization tools, and decision-support systems.
• Build RAG pipelines using embeddings, chunking strategies, vector databases, semantic retrieval, reranking, response grounding, and citation patterns.
• Integrate AI capabilities with AWS-hosted platform components, including model APIs, model gateways, data services, container platforms, and enterprise authentication patterns.
• Collaborate with cloud engineering teams on Terraform modules, IaC templates, environment promotion, CI/CD pipelines, release controls, and rollback procedures.
• Adapt and optimize models using LoRA, PEFT, instruction tuning, distillation, transfer learning, quantization, and domain adaptation techniques where appropriate.
• Optimize inference workloads for latency, throughput, token efficiency, cost, reliability, and user experience.
• Implement model and application observability, including prompt logs, retrieval quality, hallucination indicators, drift signals, feedback loops, cost telemetry, and service health.
• Embed security, privacy, Responsible AI, and model risk controls into AI application design and delivery.
• Create production documentation, runbooks, release notes, test evidence, and audit-ready implementation records.

Must-have candidate profile

• 7+ years in AI/ML engineering, platform engineering, software engineering, or applied machine learning.
• Hands-on experience with LLMs, transformers, embeddings, RAG, semantic search, and GenAI application patterns.
• Strong Python engineering skills with PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks.
• Experience deploying production AI services using APIs, containers, Kubernetes, CI/CD, cloud-native services, and monitoring platforms.
• Practical exposure to AWS AI/cloud services or comparable cloud-native AI deployment experience, with ability to ramp quickly on AWS-hosted AIRP patterns.
• Working knowledge of Terraform/IaC, DevOps pipelines, release management, model evaluation, inference optimization, and secure data handling.

Preferred Experience

• Banking, risk, compliance, financial crime, operations, or enterprise technology background.
• Experience with AWS Bedrock, SageMaker, OpenSearch, Kendra, Lambda, EKS/ECS, Azure OpenAI, Vertex AI, Databricks, vLLM, Triton, MLflow, Kubeflow, or model gateways.
• Exposure to cloud-agnostic application patterns, reusable IaC modules, model risk, AI governance, audit controls, AI cost governance, and private or open-source LLM deployments.

NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this role will depend on the nature of the role offered and will either be [$139,872 - $209,808], or [$80-$100] if the role is hired as a temporary position. Actual compensation will depend on a number of factors, including the candidate’s relevant experience, technical skills, and other qualifications.

This position may also be eligible for incentive compensation based on individual and/or company performance. If the position offered in temporary, the position will not be eligible for incentive compensation.

This position is eligible for company benefits that will depend on the nature of the role offered.

• medical
• dental
• vision insurance
• flexible spending or health savings account
• life and AD&D insurance
• short term disability coverage
• long term disability coverage
• paid time off
• employee assistance
• participation in a 401k program with company match
• additional voluntary or legally-required benefits

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees.

NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us.

NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EOO rights under the law, please click here. For Pay Transparency information, please click here.