AI Engineer - Data Engineer

Fortegra•Woodbridge Township, NJ

28d•Onsite

About The Position

Fortegra is seeking an Internal AI Forward Deployed Software Engineer to stay ahead of cutting-edge AI developments, rapidly prototype proofs-of-concept (POCs), and advise the organization's various technology teams on integrating the best AI solutions into their platforms and products. This role will be the go-to expert in bridging emerging AI technologies with internal tech needs, enabling nimble adoption across teams and deploying AI apps in production. The position operates with flexibility across software and data initiatives, contributing where business needs and priorities are most critical, adapting readily to support both software engineering and data-focused projects as priorities and requirements shift. Data-focused projects involve supporting data infrastructure in terms of platform enhancements or building new data processes to support business needs.

Requirements

Bachelor’s degree in Computer Science or a related field required
3 to 5 years of software engineering experience, including hands-on development of AI-enabled applications and solutions using modern cloud-based AI platforms such as Azure Machine Learning or Azure AI Studio. Experience with Azure is strongly preferred.
Proven track record of rapidly building POCs and advising on AI integration strategies, with strong knowledge of current AI trends, leading model families, evaluation approaches, and practical enterprise use cases.
Experience with developer tooling such as Claude Code, GitHub Copilot, and Cursor is required.
Strong full-stack engineering skills, including proficiency in React-based web development and the ability to review, understand, and refine AI-generated code.
Experience working with frontier models from providers such as OpenAI, Anthropic, and Google within a Git-based development environment.
Demonstrated ability to work with speed and flexibility across multiple priorities, debug complex AI-driven systems, and deliver effective solutions under tight timelines.
Strong communication and stakeholder management skills, with the ability to work effectively in matrixed organizations and translate complex technical concepts for both technical and non-technical audiences.
Clear commitment to continuous learning, with an established habit of staying current on AI developments through research papers, newsletters, hands-on experimentation, and industry forums.

Nice To Haves

Master’s degree in Computer Science or a related discipline with a focus on AI or machine learning is preferred.
Experience with Azure is strongly preferred.
Experience designing or implementing agentic workflows is highly valued.
Familiarity with FastAPI is preferred.
Familiarity with GitHub-based CI/CD workflows and the use of AI tools for automated testing, including tools such as Playwright, is strongly preferred.
Insurance or Financial Services domain experience
Experience building AI-enabled products or developer tooling
Familiarity with LLMs, AI agents, and prompt engineering
Experience with serverless and cloud-native architectures

Responsibilities

Monitor and stay current with the AI technology landscape, including new models, frameworks, tools, and research across areas such as LLMs, multimodal AI, agentic systems, and orchestration platforms, to inform internal recommendations and solution design.
Operate with flexibility across software and data initiatives, contributing where business needs and priorities are most critical. Adapting readily to support both software engineering and data-focused projects as priorities and requirements shift will be integral to the role. Data-focused projects involve supporting our data infrastructure in terms of platform enhancements or building new data processes to support business needs.
Engage with internal stakeholders to identify high-value AI opportunities, define use cases, and rapidly prototype tailored solutions that integrate with our APIs, data pipelines, and internal platforms for workflows such as analytics, automation, and decision support.
Advise teams on the selection and implementation of AI solutions by assessing trade-offs across accuracy, latency, scalability, security, and cost, and guide the evolution of prototypes into production-ready applications.
Own end-to-end delivery of AI initiatives, from ideation and scoping through prototyping, testing, deployment, monitoring, and iterative optimization in internal production environments. Build a sharp eye for continuously validating AI-driven processes and evaluating their outputs for accuracy, effectiveness, and trustworthiness.
Identify reusable patterns, shared components, and platform enhancement opportunities emerging from AI projects, and partner with core engineering teams to improve maintainability, scalability, security, and operational resilience.
Conduct workshops, demos, and knowledge-sharing sessions to educate teams on AI best practices, emerging tools, and Fortegra's evolving AI capabilities, helping drive organization-wide adoption and responsible usage.
Operate effectively across multiple high-priority initiatives, contributing as an engineer, technical advisor, researcher, and communicator in a fast-moving and often ambiguous environment.