Senior Level AI Research Engineer Jobs
Senior level ai research engineer jobs place experienced researchers in charge of defining model architectures, owning research agendas, and leading the teams and projects that push applied AI forward. Roles concentrate in Technology & Software, Science & Research, and Banking & Financial Services, with a strong 28% remote and hybrid share, and employers like Articul8, NVIDIA, and Databricks hiring at this level now.
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Showing 5 of 42+ Senior Level AI Research Engineer 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
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Find JobsSenior Level AI Research Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software21
- Science & Research9
- Banking & Financial Services6
- Electronics & Hardware3
- Investment & Asset Management3
Senior Level AI Research Engineer Jobs: Frequently Asked Questions
How do I get a senior level ai research engineer job?
Employers at this level look for a demonstrated research portfolio, meaning published work, patents, or shipping models at scale that others can point to. Beyond technical depth in areas like deep learning, reinforcement learning, or large language models, hiring teams expect candidates to show they have shaped a project direction, mentored junior researchers, and communicated findings to cross-functional stakeholders. A strong GitHub presence and citations help.
Which companies hire senior level ai research engineers?
Companies hiring senior level ai research engineers right now include Articul8, NVIDIA, and Databricks, based on current listings on Migrate Mate as of September 2026. Hiring at this level covers large technology firms running foundational model programs, well-funded AI startups scaling research teams, and enterprise companies embedding AI into core products.
Are there remote senior level ai research engineer jobs?
Yes, and it is more common at this level than in many other engineering disciplines. About 28% of senior level ai research engineer openings are remote or hybrid as of September 2026, reflecting both the knowledge-work nature of the role and the competitive market for senior research talent that pushes employers to drop location requirements.
What makes an ai research engineer role senior level?
A senior level role shifts ownership from executing assigned tasks to setting technical direction. That means selecting research approaches, defining evaluation frameworks, and making architectural decisions that junior engineers implement. Senior ai research engineers are also expected to mentor team members, lead collaborations across product and engineering, and represent the team's work in leadership or external forums.
Which industries hire the most senior level ai research engineers?
Senior level ai research engineer roles concentrate in Technology & Software, Science & Research, and Banking & Financial Services, based on current listings on Migrate Mate as of September 2026. Those sectors drive the most hiring because they are either building AI as a core product or deploying large-scale models to automate high-value workflows where research-grade expertise is required.