Senior Level AI Research Scientist Jobs
Senior level ai research scientist jobs place experienced researchers in charge of defining problem framing, owning model development end to end, and leading the teams that bring foundational and applied work to production. Openings skew toward 22% remote and hybrid settings across Technology & Software, Banking & Financial Services, and Healthcare & Medical Services, with employers like NVIDIA, Gartner, and Northwest Bank hiring at this level now.
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Showing 5 of 22+ Senior Level AI Research Scientist jobs
🚀 Hiring: Principal AI Engineer
We’re looking for a hands-on Principal AI Engineer to join a brand-new AI engineering organization building innovative GenAI/LLM solutions for a leading financial services organization. This is a greenfield opportunity where you’ll help shape the technical strategy, architecture, engineering standards, and AI capabilities from the ground up.
📍 Location: Covington, KY
🏢 Work Model: Onsite (5 Days in a week)
📌 Experience: 8+ years of software engineering experience with a Bachelor's degree or equivalent experience
🔥 What You'll Do
- Architect and build production-grade AI/GenAI applications from concept through deployment
- Develop solutions using LLMs, AI agents, RAG, semantic search, and workflow automation
- Design scalable enterprise AI platforms and distributed systems
- Partner with product, business, data science, architecture, and engineering teams to identify high-value AI use cases
- Establish engineering best practices and technical standards for a new AI organization
- Mentor engineers and provide technical leadership across teams
- Build secure, reliable, cloud-native applications at enterprise scale
- Translate emerging AI capabilities into practical business solutions that improve productivity and automate workflows
🧠 Top Skills
1️⃣ AI & LLM Engineering
- OpenAI
- Claude / Anthropic
- Gemini
- AWS Bedrock
- LangChain
- LangGraph
- CrewAI
- Python
- AI Agents / Agentic AI
- RAG
- Prompt Engineering
- Workflow Automation
2️⃣ Data Engineering & AI Data Foundations
- Snowflake
- Databricks
- Data Pipelines
- ETL / ELT
- Pinecone
- Weaviate
- Chroma
- Semantic Search
- Knowledge Retrieval
- Enterprise Data Architecture
3️⃣ Cloud Architecture, Scale & Security
- AWS / Azure
- Docker
- Kubernetes
- Terraform
- Microservices
- Cloud-Native Architecture
- Distributed Systems
- Security & Scalability
⭐ Ideal Background
We’re looking for someone who is more than an AI developer — you should be a Principal-level technical leader who can architect, build, and take AI solutions into production. The ideal candidate brings:
- Strong GenAI/LLM engineering experience
- Hands-on experience building RAG and agentic AI solutions
- Strong Python/software engineering background
- Enterprise data engineering experience
- Cloud architecture and distributed systems expertise
- Experience with containers, Kubernetes, and Infrastructure-as-Code
- Strong architecture and system-design skills
- Experience mentoring engineers and influencing technical direction
- Ability to work directly with business and product stakeholders
- Experience taking AI solutions from POC → production
💡 Example AI Use Cases
The team will work on solutions such as:
- Automated meeting preparation and research
- Intelligent call summarization and insight generation
- Automated follow-up and workflow orchestration
- Enterprise knowledge retrieval and recommendation systems
- AI-assisted decision support
- Productivity and workflow automation using enterprise data
📞 Interview Process
2–3 rounds
1. Initial Zoom/phone screen
2. Technical interview with engineering/architecture team
3. Product/business discussion
If you're a Principal/Staff-level AI Engineer who wants to help build an AI organization from the ground up, I'd love to connect.
📩 Interested? Send me your resume on abhishek.bisht@mastechdigital.com or apply on this job post.
Hiring #AIJobs #PrincipalEngineer #AIEngineer #GenerativeAI #GenAI #LLM #ArtificialIntelligence #RAG #AIAgents #LangChain #LangGraph #Python #AWS #Azure #Kubernetes #Snowflake #Databricks #CloudArchitecture #MachineLearning #TechJobs #KentuckyJobs #CovingtonKY
🚀 Hiring: Principal AI Engineer
We’re looking for a hands-on Principal AI Engineer to join a brand-new AI engineering organization building innovative GenAI/LLM solutions for a leading financial services organization. This is a greenfield opportunity where you’ll help shape the technical strategy, architecture, engineering standards, and AI capabilities from the ground up.
📍 Location: Covington, KY
🏢 Work Model: Onsite (5 Days in a week)
📌 Experience: 8+ years of software engineering experience with a Bachelor's degree or equivalent experience
🔥 What You'll Do
- Architect and build production-grade AI/GenAI applications from concept through deployment
- Develop solutions using LLMs, AI agents, RAG, semantic search, and workflow automation
- Design scalable enterprise AI platforms and distributed systems
- Partner with product, business, data science, architecture, and engineering teams to identify high-value AI use cases
- Establish engineering best practices and technical standards for a new AI organization
- Mentor engineers and provide technical leadership across teams
- Build secure, reliable, cloud-native applications at enterprise scale
- Translate emerging AI capabilities into practical business solutions that improve productivity and automate workflows
🧠 Top Skills
1️⃣ AI & LLM Engineering
- OpenAI
- Claude / Anthropic
- Gemini
- AWS Bedrock
- LangChain
- LangGraph
- CrewAI
- Python
- AI Agents / Agentic AI
- RAG
- Prompt Engineering
- Workflow Automation
2️⃣ Data Engineering & AI Data Foundations
- Snowflake
- Databricks
- Data Pipelines
- ETL / ELT
- Pinecone
- Weaviate
- Chroma
- Semantic Search
- Knowledge Retrieval
- Enterprise Data Architecture
3️⃣ Cloud Architecture, Scale & Security
- AWS / Azure
- Docker
- Kubernetes
- Terraform
- Microservices
- Cloud-Native Architecture
- Distributed Systems
- Security & Scalability
⭐ Ideal Background
We’re looking for someone who is more than an AI developer — you should be a Principal-level technical leader who can architect, build, and take AI solutions into production. The ideal candidate brings:
- Strong GenAI/LLM engineering experience
- Hands-on experience building RAG and agentic AI solutions
- Strong Python/software engineering background
- Enterprise data engineering experience
- Cloud architecture and distributed systems expertise
- Experience with containers, Kubernetes, and Infrastructure-as-Code
- Strong architecture and system-design skills
- Experience mentoring engineers and influencing technical direction
- Ability to work directly with business and product stakeholders
- Experience taking AI solutions from POC → production
💡 Example AI Use Cases
The team will work on solutions such as:
- Automated meeting preparation and research
- Intelligent call summarization and insight generation
- Automated follow-up and workflow orchestration
- Enterprise knowledge retrieval and recommendation systems
- AI-assisted decision support
- Productivity and workflow automation using enterprise data
📞 Interview Process
2–3 rounds
1. Initial Zoom/phone screen
2. Technical interview with engineering/architecture team
3. Product/business discussion
If you're a Principal/Staff-level AI Engineer who wants to help build an AI organization from the ground up, I'd love to connect.
📩 Interested? Send me your resume on abhishek.bisht@mastechdigital.com or apply on this job post.
Hiring #AIJobs #PrincipalEngineer #AIEngineer #GenerativeAI #GenAI #LLM #ArtificialIntelligence #RAG #AIAgents #LangChain #LangGraph #Python #AWS #Azure #Kubernetes #Snowflake #Databricks #CloudArchitecture #MachineLearning #TechJobs #KentuckyJobs #CovingtonKY
See All 22 Senior Level AI Research Scientist Jobs
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Find JobsSenior Level AI Research Scientist Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software12
- Banking & Financial Services5
- Healthcare & Medical Services2
- Investment & Asset Management2
- Fintech1
Senior Level AI Research Scientist Jobs: Frequently Asked Questions
How do I get a senior level ai research scientist job?
Employers hiring at the senior level look for candidates who have shipped research to production, not just published it. A strong publication record matters, but so does demonstrated ownership of a full project lifecycle, from problem definition through deployment. The clearest edge comes from showing you've shaped a research agenda, mentored junior researchers, and made architectural decisions that held up at scale.
Which companies hire senior level ai research scientists?
Companies hiring senior level ai research scientists right now include NVIDIA, Gartner, and Northwest Bank, based on current listings on Migrate Mate as of September 2026. Hiring at this level is concentrated among organizations with dedicated research labs, large-scale ML infrastructure, and the budget to support long-horizon work alongside applied product goals.
Are there remote senior level ai research scientist jobs?
Yes, though availability varies by employer and research focus. About 22% of senior level ai research scientist openings are remote or hybrid as of September 2026, reflecting the field's strong orientation toward distributed, asynchronous work. Roles tied to proprietary hardware, robotics, or lab-based experimentation are more likely to require on-site presence.
What makes an ai research scientist role senior level?
Senior level ai research scientist roles are defined by ownership and scope rather than task execution. At this stage, you set the technical direction for a research area, make independent decisions on methodology and infrastructure, and are expected to mentor junior scientists and contribute to hiring. The work goes beyond implementing known approaches to advancing them, with direct accountability for research outcomes.
Which industries hire the most senior level ai research scientists?
Senior level ai research scientist roles concentrate in Technology & Software, Banking & Financial Services, and Healthcare & Medical Services, based on current listings on Migrate Mate as of September 2026. These sectors invest heavily at this level because they have both the data infrastructure and the competitive pressure that make foundational research directly valuable to core business outcomes.