Note: The job is a remote job and is open to candidates in USA. NTT DATA North America is a recognized leader in IT and business services, and they are seeking an AI Foundation Model Engineer to join their team. The role involves designing, building, deploying, and optimizing enterprise-grade AI systems powered by foundation models and ensuring secure, scalable production systems on their AI-ready platform.
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
- 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
- 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
Benefits
- Company benefits (depend on the nature of the role offered)
- Medical, dental, and vision insurance
- Flexible spending or health savings account
- Life and AD&D insurance
- Short-and long-term disability coverage
- Paid time off
- Employee assistance
- Participation in a 401k program with company match
- Additional voluntary or legally required benefits
Company Overview
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