AI Product Engineer Visa Sponsorship Jobs in North Carolina
North Carolina's growing tech sector, anchored by Research Triangle Park and companies like Red Hat, Lenovo, and Cisco, creates steady demand for AI Product Engineers. Raleigh, Durham, and Charlotte are the primary hiring hubs. Many employers in the region have active H-1B visa sponsorship histories, making North Carolina one of the more active states for this role.
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Get Access To All JobsINTRODUCTION
Capgemini is at the forefront of Generative AI innovation, helping Financial Services clients industrialize GenAI and Agentic AI platforms at enterprise scale.
We are seeking an experienced and innovative AI Product Engineer – Agentic Platforms to join our Financial Services Artificial Intelligence & Business Lines (FS‑ABL) practice. This role is ideal for a consulting technologist with deep expertise in modern GenAI tooling, agentic system design, and enterprise SDLC, who can partner directly with clients to envision, design, develop, and deploy Agentic AI platforms in regulated environments.
In this role, you will work at the intersection of client advisory, AI product engineering, and delivery execution, helping banks, insurers, and capital markets firms transition from GenAI pilots to production‑grade, governed, multi‑agent systems. You will apply leading GenAI frameworks and LLM platforms — including Anthropic, OpenAI, LangChain, LangGraph, DSPy, and vector databases—while operating across the full Agentic SDLC.
P&C Insurance knowledge and experience is a significant plus. Additionally, familiarity with core insurance platforms like Guidewire, DuckCreek or Majesco will be extremely helpful to succeed in this role.
We are looking for candidates across all levels of experience and expertise - junior through senior level AI Product Engineers.
CLIENT ADVISORY & PRODUCT VISION
- Partner directly with Financial Services clients to identify, prioritize, and shape Agentic AI use cases across customer operations, underwriting, claims, risk, compliance, finance, and technology.
- Lead client workshops to define agent personas, responsibilities, autonomy boundaries, human‑in‑the‑loop checkpoints, and escalation logic.
- Translate evolving business needs into agentic product backlogs, roadmaps, and MVP definitions.
- Support executive conversations around GenAI platform strategy, operating models, vendor selection, and scale‑out approaches.
AGENTIC PLATFORM & ARCHITECTURE DESIGN
- Design and implement multi‑agent architectures using modern GenAI tooling, including:
- Planner, executor, reviewer/critic, and supervisor agents
- Tool‑calling and function‑calling agents
- Memory‑enabled agents (conversation, semantic, episodic, and structured memory)
- Leverage LangChain and LangGraph for agent orchestration, workflows, and control flow.
- Apply DSPy and declarative prompt optimization techniques for repeatability, performance tuning, and regression control.
- Design agent interaction patterns such as hierarchical agents, collaborating agents, and event‑driven agent workflows.
- Define standardized agent contracts, interfaces, and schemas to enable reuse and scale.
AGENTIC SDLC & ENGINEERING DELIVERY
- Own delivery across the full Software Development Lifecycle (SDLC), extending it into a formal Agentic SDLC, including:
- Agent design specifications and behavior contracts
- Prompt, policy, and tool versioning
- Simulation environments and offline evaluation
- Automated testing of agent flows and guardrails
- Controlled rollout, telemetry‑driven optimization, and continuous learning
- Build production‑grade AI services primarily using Python, integrating:
- LLM providers such as Anthropic (Claude), OpenAI, and open‑source models
- Retrieval‑Augmented Generation (RAG) using vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate)
- Implement CI/CD pipelines for agent code, prompts, and policies.
- Integrate GenAI agents with client systems via APIs, workflow engines, event streams, and data platforms.
OBSERVABILITY, EVALUATION & OPTIMIZATION
- Implement agent observability including tracing, decision logging, tool usage, and failure analysis.
- Apply evaluation frameworks for hallucination detection, consistency checks, and fitness scoring.
- Design feedback loops incorporating human‑in‑the‑loop review and reinforcement.
- Monitor cost, latency, throughput, and behavioral drift across deployed agents.
GOVERNANCE, RISK & FINANCIAL SERVICES COMPLIANCE
- Design Agentic AI platforms aligned with Financial Services regulatory expectations, including:
- Auditability and traceability of agent decisions
- Model and prompt explainability
- Data privacy and security controls
- Resilience and fail‑safe mechanisms
- Embed guardrails and policies addressing hallucination risk, bias, unauthorized actions, and escalation failures.
- Produce documentation supporting risk, compliance, internal audit, and regulator engagement.
TEAM LEADERSHIP & FIRM CONTRIBUTION
- Provide technical leadership and mentorship to consulting delivery teams.
- Contribute to internal GenAI accelerators, agent frameworks, and reusable assets.
- Support RFPs, proposals, and client solution designs with credible GenAI and agentic architectures.
- Participate in thought leadership on Agentic SDLC, GenAI engineering, and responsible autonomy.
BENEFITS
This position comes with competitive compensation and benefits package:
- Competitive salary and performance‑based bonuses
- Comprehensive benefits package
- Career development and training opportunities
- Flexible work arrangements (remote and/or office‑based)
- Dynamic and inclusive work culture within a globally known group
- Private Health Insurance
- Retirement Benefits
- Paid Time Off
- Training & Development
- Note: Benefits differ based on employee level
ABOUT CAPGEMINI
Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 420,000 team members in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group €22.5 billion in revenues in 2025.
INTRODUCTION
Capgemini is at the forefront of Generative AI innovation, helping Financial Services clients industrialize GenAI and Agentic AI platforms at enterprise scale.
We are seeking an experienced and innovative AI Product Engineer – Agentic Platforms to join our Financial Services Artificial Intelligence & Business Lines (FS‑ABL) practice. This role is ideal for a consulting technologist with deep expertise in modern GenAI tooling, agentic system design, and enterprise SDLC, who can partner directly with clients to envision, design, develop, and deploy Agentic AI platforms in regulated environments.
In this role, you will work at the intersection of client advisory, AI product engineering, and delivery execution, helping banks, insurers, and capital markets firms transition from GenAI pilots to production‑grade, governed, multi‑agent systems. You will apply leading GenAI frameworks and LLM platforms — including Anthropic, OpenAI, LangChain, LangGraph, DSPy, and vector databases—while operating across the full Agentic SDLC.
P&C Insurance knowledge and experience is a significant plus. Additionally, familiarity with core insurance platforms like Guidewire, DuckCreek or Majesco will be extremely helpful to succeed in this role.
We are looking for candidates across all levels of experience and expertise - junior through senior level AI Product Engineers.
CLIENT ADVISORY & PRODUCT VISION
- Partner directly with Financial Services clients to identify, prioritize, and shape Agentic AI use cases across customer operations, underwriting, claims, risk, compliance, finance, and technology.
- Lead client workshops to define agent personas, responsibilities, autonomy boundaries, human‑in‑the‑loop checkpoints, and escalation logic.
- Translate evolving business needs into agentic product backlogs, roadmaps, and MVP definitions.
- Support executive conversations around GenAI platform strategy, operating models, vendor selection, and scale‑out approaches.
AGENTIC PLATFORM & ARCHITECTURE DESIGN
- Design and implement multi‑agent architectures using modern GenAI tooling, including:
- Planner, executor, reviewer/critic, and supervisor agents
- Tool‑calling and function‑calling agents
- Memory‑enabled agents (conversation, semantic, episodic, and structured memory)
- Leverage LangChain and LangGraph for agent orchestration, workflows, and control flow.
- Apply DSPy and declarative prompt optimization techniques for repeatability, performance tuning, and regression control.
- Design agent interaction patterns such as hierarchical agents, collaborating agents, and event‑driven agent workflows.
- Define standardized agent contracts, interfaces, and schemas to enable reuse and scale.
AGENTIC SDLC & ENGINEERING DELIVERY
- Own delivery across the full Software Development Lifecycle (SDLC), extending it into a formal Agentic SDLC, including:
- Agent design specifications and behavior contracts
- Prompt, policy, and tool versioning
- Simulation environments and offline evaluation
- Automated testing of agent flows and guardrails
- Controlled rollout, telemetry‑driven optimization, and continuous learning
- Build production‑grade AI services primarily using Python, integrating:
- LLM providers such as Anthropic (Claude), OpenAI, and open‑source models
- Retrieval‑Augmented Generation (RAG) using vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate)
- Implement CI/CD pipelines for agent code, prompts, and policies.
- Integrate GenAI agents with client systems via APIs, workflow engines, event streams, and data platforms.
OBSERVABILITY, EVALUATION & OPTIMIZATION
- Implement agent observability including tracing, decision logging, tool usage, and failure analysis.
- Apply evaluation frameworks for hallucination detection, consistency checks, and fitness scoring.
- Design feedback loops incorporating human‑in‑the‑loop review and reinforcement.
- Monitor cost, latency, throughput, and behavioral drift across deployed agents.
GOVERNANCE, RISK & FINANCIAL SERVICES COMPLIANCE
- Design Agentic AI platforms aligned with Financial Services regulatory expectations, including:
- Auditability and traceability of agent decisions
- Model and prompt explainability
- Data privacy and security controls
- Resilience and fail‑safe mechanisms
- Embed guardrails and policies addressing hallucination risk, bias, unauthorized actions, and escalation failures.
- Produce documentation supporting risk, compliance, internal audit, and regulator engagement.
TEAM LEADERSHIP & FIRM CONTRIBUTION
- Provide technical leadership and mentorship to consulting delivery teams.
- Contribute to internal GenAI accelerators, agent frameworks, and reusable assets.
- Support RFPs, proposals, and client solution designs with credible GenAI and agentic architectures.
- Participate in thought leadership on Agentic SDLC, GenAI engineering, and responsible autonomy.
BENEFITS
This position comes with competitive compensation and benefits package:
- Competitive salary and performance‑based bonuses
- Comprehensive benefits package
- Career development and training opportunities
- Flexible work arrangements (remote and/or office‑based)
- Dynamic and inclusive work culture within a globally known group
- Private Health Insurance
- Retirement Benefits
- Paid Time Off
- Training & Development
- Note: Benefits differ based on employee level
ABOUT CAPGEMINI
Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 420,000 team members in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group €22.5 billion in revenues in 2025.
AI Product Engineer Job Roles in North Carolina
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Search AI Product Engineer Jobs in North CarolinaAI Product Engineer Jobs in North Carolina: Frequently Asked Questions
Which companies sponsor visas for AI Product Engineers in North Carolina?
Several large employers in North Carolina have documented H-1B sponsorship histories for engineering roles involving AI and product development. These include Red Hat in Raleigh, Lenovo's North American headquarters in Morrisville, Cisco's Research Triangle offices, and SAS Institute in Cary. Financial technology firms in Charlotte, including Bank of America and Wells Fargo, also sponsor AI-focused engineering positions.
Which visa types are most common for AI Product Engineer roles in North Carolina?
The H-1B is by far the most common visa category for AI Product Engineers in North Carolina, as the role typically qualifies as a specialty occupation requiring a bachelor's degree or higher in computer science, engineering, or a related field. Employers may also sponsor L-1B visas for intracompany transfers. Candidates with an active O-1A petition may find opportunities with larger tech employers in the Research Triangle area.
Which cities in North Carolina have the most AI Product Engineer sponsorship jobs?
Raleigh and the broader Research Triangle Park corridor, which includes Durham and Cary, account for the largest concentration of AI Product Engineer sponsorship opportunities in North Carolina. Charlotte is the second major hub, driven by its financial services and fintech sectors. Smaller but growing pockets of tech hiring exist in Morrisville, Chapel Hill, and Wilmington, particularly among software and health tech companies.
How to find ai product engineer visa sponsorship jobs in North Carolina?
Migrate Mate is built specifically for international job seekers and filters AI Product Engineer roles by visa sponsorship status, so you can browse North Carolina-specific openings without sifting through positions that don't offer sponsorship. The platform focuses on verified sponsoring employers, which is particularly useful for targeting Research Triangle Park companies and Charlotte-area tech and finance firms known to sponsor H-1B candidates.
Are there state-specific factors AI Product Engineers should know about sponsorship in North Carolina?
North Carolina's university pipeline, particularly from NC State, Duke, and UNC Chapel Hill, feeds a competitive talent market for AI and machine learning roles. Employers in Research Triangle Park are generally experienced with visa sponsorship processes given the area's long history of attracting international talent. SAS Institute and Red Hat in particular have well-established immigration support infrastructure, which can make the sponsorship process more predictable for candidates joining those organizations.
What is the prevailing wage for sponsored ai product engineer jobs in North Carolina?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.