Senior Level AI Engineer Jobs
Senior level ai engineer jobs put experienced professionals in charge of model architecture, technical roadmaps, and the cross-functional teams that bring AI systems into production. Roles are concentrated across Technology & Software, Consulting & Professional Services, and Banking & Financial Services, with a mix of on-site, remote, and hybrid settings, and employers like CVS Health, Google, and NVIDIA hiring at this level now.
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At NTT DATA, we know that with the right people on board, anything is possible. The quality, integrity, and commitment of our employees have been key factors in our company's growth and market presence. By hiring the best people and helping them grow both professionally and personally, we ensure a bright future for NTT DATA and for the people who work here.
For more than 25 years, NTT DATA Services have focused on impacting the core of your business operations with industry-leading outsourcing services and automation. With our industry-specific platforms, we deliver continuous value addition, and innovation that will improve your business outcomes. Outsourcing is not just a method of gaining a one-time cost advantage, but an effective strategy for gaining and maintaining competitive advantages when executed as part of an overall sourcing strategy.
NTT DATA Services currently seeks a AI Foundation Model Engineer to join our team in Jersey City, New Jersey.
Role purpose
Design, build, deploy, and optimize enterprise-grade AI systems powered by foundation models, LLMs, retrieval-augmented generation, and agentic AI workflows. The role converts AI concepts into secure, scalable, observable, and supportable production systems suitable for a regulated financial-services environment.
Primary ownership
- Production LLM applications, RAG pipelines, AI services, and model-serving integrations.
- End-to-end LLMOps/MLOps lifecycle from experimentation to deployment, monitoring, evaluation, rollback, and continuous improvement.
- Model adaptation, inference optimization, APIs, observability, and operational readiness for GenAI solutions.
- 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.
- Adapt and optimize models using LoRA, PEFT, instruction tuning, distillation, transfer learning, quantization, and domain adaptation techniques.
- Develop scalable APIs, microservices, model-serving components, and integration patterns across cloud, hybrid, or containerized environments.
- 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.
- 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 knowledge of model evaluation, fine-tuning, inference optimization, and secure data handling.
- Banking, risk, compliance, financial crime, operations, or enterprise technology background.
- Experience with Azure OpenAI, AWS Bedrock, Vertex AI, Databricks, vLLM, Triton, MLflow, Kubeflow, or model gateways. Exposure to model risk, AI governance, audit controls, AI cost governance, and private or open-source LLM deployments
About NTT DATA Services:
NTT DATA Services is a recognized leader in IT and business services, including cloud, data and applications, headquartered in Texas. As part of NTT DATA, a $30 billion trusted global innovator with a combined global reach of over 80 countries, we help clients transform through business and technology consulting, industry and digital solutions, applications development and management, managed edge-to-cloud infrastructure services, BPO, systems integration and global data centers. We are committed to our clients' long-term success. Visit nttdata.com or LinkedIn to learn more.
NTT DATA Services is an equal opportunity employer and considers all applicants without regarding to race, color, religion, citizenship, national origin, ancestry, age, sex, sexual orientation, gender identity, genetic information, physical or mental disability, veteran or marital status, or any other characteristic protected by law. We are committed to creating a diverse and inclusive environment for all employees. If you need assistance or an accommodation due to a disability, please inform your recruiter so that we may connect you with the appropriate team.
NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this role is $80/hr - $88/hr. Actual compensation will depend on a number of factors, including the candidate's relevant experience, technical skills, and other qualifications.
This position is eligible for company benefits including participation in medical, dental, and vision insurance, flexible spending or health savings account, and AD&D insurance, employee assistance, participation in a 401k program, and additional voluntary or legally-required benefits
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Who's Hiring
- CVS Health75
- Google59
- NVIDIA53
- Capital One45
- JPMorganChase36
Top Industries Hiring
- Technology & Software824
- Consulting & Professional Services168
- Banking & Financial Services144
- Electronics & Hardware136
- Healthcare & Medical Services126
Senior Level AI Engineer Jobs: Frequently Asked Questions
How do I get a senior level ai engineer job?
Employers hiring at this level look for candidates who have owned the full lifecycle of production AI systems, not just contributed to them. Demonstrating that you have set technical direction, resolved ambiguous problems at scale, and mentored junior engineers gives you a clear edge. A portfolio of shipped models and published or presentable work on complex architectures strengthens any application significantly.
Which companies hire senior level ai engineers?
Companies hiring senior level ai engineers right now include CVS Health, Google, and NVIDIA, based on current listings on Migrate Mate as of July 2026. Hiring at this level comes from a wide range, including large technology firms, enterprise software companies, financial institutions, and well-funded startups building AI-first products.
Are there remote senior level ai engineer jobs?
Yes, remote and hybrid options are common at this level. About 41% of senior level ai engineer openings are remote or hybrid as of July 2026, reflecting how many organizations treat experienced AI engineers as distributed-first talent. On-site roles tend to concentrate in companies with sensitive data environments or hands-on hardware requirements.
What makes an ai engineer role senior level?
Senior level roles are defined by scope and ownership rather than task execution. At this stage, you are expected to design system architecture, set standards the team follows, drive decisions that affect product direction, and mentor engineers at earlier career stages. The problems are less defined, the tradeoffs are higher stakes, and the accountability for outcomes sits with you.
Which industries hire the most senior level ai engineers?
Senior level ai engineer roles concentrate in Technology & Software, Consulting & Professional Services, and Banking & Financial Services, based on current listings on Migrate Mate as of July 2026. These sectors drive hiring because they are deploying AI at scale across core business functions, creating sustained demand for engineers who can lead that work rather than simply contribute to it.