AI Solutions Engineer Jobs in New Jersey
AI Solutions Engineer jobs in New Jersey are in strong and growing demand, concentrated in life sciences, financial services, and enterprise technology sectors, with openings at every level from associate through principal and staff engineer. The most active hiring metros are Newark, Princeton, and Jersey City, where major employers including IBM, Cognizant, and Johnson & Johnson maintain significant operations. Cloud integration, natural language processing, and enterprise AI deployment are the most sought-after specialties across New Jersey postings. Find a role that fits below and apply directly.
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Showing 5 of 24+ AI Solutions Engineer jobs
This is a highly collaborative, stakeholder-facing role requiring the ability to translate business requirements into secure, scalable, and production-ready AI solutions.
Key Responsibilities
- Design and develop enterprise AI/LLM applications, assistants, agents, and intelligent workflows.
- Build scalable and production-ready solutions using Python and modern software engineering practices.
- Develop agentic AI workflows using frameworks such as LangGraph or similar orchestration technologies.
- Implement tool integrations using MCP/FastMCP or comparable protocols and frameworks.
- Build and integrate REST APIs, enterprise systems, databases, and SQL-based solutions.
- Develop RAG (Retrieval-Augmented Generation) solutions using structured and unstructured data sources.
- Design secure data-access patterns incorporating authentication, authorization, and enterprise security requirements.
- Implement AI evaluation, monitoring, tracing, and observability using tools such as LangSmith, Weights & Biases (W&B), OpenTelemetry, or similar platforms.
- Establish mechanisms to evaluate LLM accuracy, reliability, latency, cost, and overall application performance.
- Incorporate Human-in-the-Loop (HITL) processes into AI workflows where appropriate.
- Apply principles of AI governance, responsible AI, privacy, security, and compliance throughout the development lifecycle.
- Collaborate directly with business stakeholders, product teams, architects, and engineering teams to identify opportunities and deliver AI solutions.
- Act as a forward-deployed engineer, working closely with stakeholders to understand problems, prototype solutions, gather feedback, and rapidly iterate.
- Troubleshoot, optimize, and continuously improve AI applications in production environments.
- Contribute to technical documentation, architecture decisions, development standards, and best practices.
- 5–8 years of professional software engineering experience.
- Strong hands-on experience with Python and software development.
- Demonstrated experience building AI/LLM-powered applications in enterprise or production environments.
- Experience developing AI assistants, agents, agentic workflows, or LLM applications.
- Hands-on experience with MCP/FastMCP or similar tool-integration technologies.
- Experience with LangGraph or comparable AI/agent orchestration frameworks.
- Strong understanding of APIs, SQL, databases, and enterprise system integration.
- Experience implementing RAG solutions using structured and/or unstructured data.
- Experience with LLM evaluation, monitoring, tracing, or observability tools such as LangSmith, W&B, OpenTelemetry, or similar.
- Understanding of authentication, authorization, secure data access, and enterprise security practices.
- Strong understanding of AI governance, responsible AI, privacy, security, and Human-in-the-Loop concepts.
- Excellent communication and stakeholder-management skills.
- Ability to work directly with customers/business stakeholders in a forward-deployed engineering capacity.
- Experience working with major LLM platforms and APIs such as OpenAI, Azure OpenAI, Anthropic, or similar.
- Experience with vector databases, embeddings, semantic search, and retrieval pipelines.
- Experience deploying AI applications in cloud environments such as Azure, AWS, or GCP.
- Familiarity with CI/CD, Git, containers, and modern DevOps practices.
- Experience building enterprise-grade AI solutions with strong emphasis on security, scalability, reliability, and governance.
- Experience working in consulting, professional services, or customer-facing engineering environments.
Python | LLMs | Generative AI | AI Agents | AI Assistants | MCP / FastMCP | LangGraph | RAG | APIs | SQL | Databases | LangSmith | W&B | OpenTelemetry | Authentication | Authorization | AI Governance | Responsible AI | HITL | Enterprise Integration
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This is a highly collaborative, stakeholder-facing role requiring the ability to translate business requirements into secure, scalable, and production-ready AI solutions.
Key Responsibilities
- Design and develop enterprise AI/LLM applications, assistants, agents, and intelligent workflows.
- Build scalable and production-ready solutions using Python and modern software engineering practices.
- Develop agentic AI workflows using frameworks such as LangGraph or similar orchestration technologies.
- Implement tool integrations using MCP/FastMCP or comparable protocols and frameworks.
- Build and integrate REST APIs, enterprise systems, databases, and SQL-based solutions.
- Develop RAG (Retrieval-Augmented Generation) solutions using structured and unstructured data sources.
- Design secure data-access patterns incorporating authentication, authorization, and enterprise security requirements.
- Implement AI evaluation, monitoring, tracing, and observability using tools such as LangSmith, Weights & Biases (W&B), OpenTelemetry, or similar platforms.
- Establish mechanisms to evaluate LLM accuracy, reliability, latency, cost, and overall application performance.
- Incorporate Human-in-the-Loop (HITL) processes into AI workflows where appropriate.
- Apply principles of AI governance, responsible AI, privacy, security, and compliance throughout the development lifecycle.
- Collaborate directly with business stakeholders, product teams, architects, and engineering teams to identify opportunities and deliver AI solutions.
- Act as a forward-deployed engineer, working closely with stakeholders to understand problems, prototype solutions, gather feedback, and rapidly iterate.
- Troubleshoot, optimize, and continuously improve AI applications in production environments.
- Contribute to technical documentation, architecture decisions, development standards, and best practices.
- 5–8 years of professional software engineering experience.
- Strong hands-on experience with Python and software development.
- Demonstrated experience building AI/LLM-powered applications in enterprise or production environments.
- Experience developing AI assistants, agents, agentic workflows, or LLM applications.
- Hands-on experience with MCP/FastMCP or similar tool-integration technologies.
- Experience with LangGraph or comparable AI/agent orchestration frameworks.
- Strong understanding of APIs, SQL, databases, and enterprise system integration.
- Experience implementing RAG solutions using structured and/or unstructured data.
- Experience with LLM evaluation, monitoring, tracing, or observability tools such as LangSmith, W&B, OpenTelemetry, or similar.
- Understanding of authentication, authorization, secure data access, and enterprise security practices.
- Strong understanding of AI governance, responsible AI, privacy, security, and Human-in-the-Loop concepts.
- Excellent communication and stakeholder-management skills.
- Ability to work directly with customers/business stakeholders in a forward-deployed engineering capacity.
- Experience working with major LLM platforms and APIs such as OpenAI, Azure OpenAI, Anthropic, or similar.
- Experience with vector databases, embeddings, semantic search, and retrieval pipelines.
- Experience deploying AI applications in cloud environments such as Azure, AWS, or GCP.
- Familiarity with CI/CD, Git, containers, and modern DevOps practices.
- Experience building enterprise-grade AI solutions with strong emphasis on security, scalability, reliability, and governance.
- Experience working in consulting, professional services, or customer-facing engineering environments.
Python | LLMs | Generative AI | AI Agents | AI Assistants | MCP / FastMCP | LangGraph | RAG | APIs | SQL | Databases | LangSmith | W&B | OpenTelemetry | Authentication | Authorization | AI Governance | Responsible AI | HITL | Enterprise Integration
UZg6fca3WX
See All 24 AI Solutions Engineer Jobs in New Jersey
Find roles in New Jersey that match your experience and apply in just a few clicks.
Find AI Solutions Engineer JobsAI Solutions Engineer Jobs by City in New Jersey
Where New Jersey roles are concentrated, by current openings.
AI Solutions Engineer Job Market in New Jersey
A snapshot from current New Jersey openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Banking & Financial Services
- Investment & Asset Management
- Fintech
- Manufacturing
What New Jersey Employers Look For
The qualifications that appear most often in AI solutions engineer jobs across New Jersey.
- Bachelor's or master's degree in computer science, AI, or a related engineering field
- Hands-on experience building and deploying machine learning models in production environments
- Proficiency with Python and major ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience integrating AI solutions with cloud platforms including AWS, Azure, or Google Cloud
- Strong client-facing communication skills for translating technical outputs into business recommendations
- Familiarity with enterprise software architectures, APIs, and data pipeline design
AI Solutions Engineer Jobs in New Jersey: Frequently Asked Questions
How do you become a ai solutions engineer in New Jersey?
The path into ai solutions engineer roles in New Jersey typically starts with a bachelor's degree in computer science, data science, or a related field, though many employers also value demonstrated project work and a strong portfolio. There is no state-issued license for this role in New Jersey. Employers here, particularly in the life sciences and financial technology corridors, look for candidates who combine cloud platform certifications from providers like AWS or Microsoft Azure with applied ML experience from internships, graduate research, or independent projects.
How much do AI solutions engineers make in New Jersey?
AI solutions engineers in New Jersey earn a median of about $135,940 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $84,880 for the lowest 10% to over $207,200 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai solutions engineers in New Jersey?
Employers hiring ai solutions engineers in New Jersey right now include JPMorganChase, Citi, and Innovative Defense Technologies, based on current listings on Migrate Mate as of September 2026. New Jersey's dense concentration of pharmaceutical, financial services, and global technology firms means demand is distributed across both Fortune 500 headquarters and large consulting delivery centers throughout the state.
Which New Jersey cities have the most ai solutions engineer jobs?
The cities with the most ai solutions engineer openings in New Jersey are Jersey City, Princeton, and Mount Laurel. Newark and Jersey City benefit from their proximity to New York City's technology and finance ecosystem, making them natural hubs for enterprise AI roles, while Princeton draws demand from the life sciences and research-intensive firms concentrated along the Route 1 corridor.
Are there remote ai solutions engineer jobs in New Jersey?
Yes, and more than most fields. About 23% of ai solutions engineer openings tied to New Jersey are remote or hybrid as of September 2026, reflecting how much of this work centers on software development, model training, and client advisory work that travels well over distributed tools. The parts of the role most commonly performed remotely are model development, data analysis, and stakeholder presentations, while on-site work tends to arise during implementation sprints or enterprise client deployments.
How can I get hired as a ai solutions engineer in New Jersey with little or no experience?
The most realistic entry path is a rotational or associate technology program at one of New Jersey's large employers: IBM, Cognizant, and several major pharmaceutical companies run structured new-graduate programs that place candidates into AI or data engineering tracks. Lateral moves from roles such as data analyst, software developer, or business intelligence engineer are common and well-recognized by hiring managers here. Building a portfolio of deployed ML projects on public repositories and earning a cloud platform certification significantly strengthens applications for candidates without formal work history in AI.
Where can I find and apply to ai solutions engineer jobs in New Jersey?
You can find and apply to ai solutions engineer jobs in New Jersey on Migrate Mate, which lists current openings across the state. Search the available roles, find the ones that fit your background and location, and apply directly to the employers posting them.
See All 24 AI Solutions Engineer Jobs in New Jersey
Find roles in New Jersey that match your experience and apply in just a few clicks.
Find AI Solutions Engineer Jobs