Lead Agentic AI Automation Engineer

Title: Lead Agentic AI Automation Engineer

Location: Iselin, NJ

Duration: 12 months

Work Engagement: W2

Work Schedule: Onsite

Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits

Summary:

In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Specialty Software Engineering. Review and analyze complex multi-faceted, larger scale, or longer-term Specialty Software Engineering challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel. Required Qualifications: Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.

Key Responsibilities:

• Lead moderately complex initiatives and deliverables within technical engineering environments

• Contribute to large scale planning of strategies across Consumer Technology

• Design, code, test, debug, and document applications and services including upgrades and deployments

• Review technical challenges that require in depth evaluation of technologies, procedures, and engineering approaches

• Resolve moderately complex issues while guiding teams to meet existing and emerging business needs

• Collaborate with peers, colleagues, and mid-level managers to resolve technical challenges and meet project goals

• Lead projects and act as an escalation point, providing direction to less experienced engineers

• Design, develop, and deploy AI applications using enterprise APIs, LLMs, agent frameworks, and related technologies

• Implement prompt engineering, retrieval augmented generation, fine tuning, and agentic design patterns

• Integrate LLM models with existing enterprise systems and ensure that AI solutions meet governance, security, and compliance standards

• Troubleshoot complex application and model related issues and contribute to the continuous improvement of AI systems

• Assist and mentor engineers in advanced software development and AI engineering practices

• Stay informed of advancements in AI, LLMs, and agent frameworks and apply relevant updates to products and systems

Key Requirements:

Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.

• Understanding of cloud security principles including identity and access management, encryption, and network security in public or hybrid cloud environments

• Experience working in highly regulated industries such as financial services

• Experience as a technical lead or architect, including mentoring senior engineers

• Experience integrating or contributing to open source AI or ML projects

• Experience integrating applications with enterprise data platforms, APIs, and secure data pipelines

• Strong communication and documentation skills to collaborate across engineering, product, and oversight teams

Preferred Skills and Experience:

• Experience with Power Platform, including Power Apps and Dataverse

• Experience with UiPath or other enterprise automation tools

• Experience with LLM development using OpenAI, Anthropic, or Google Gemini models

• Experience with agentic frameworks and AI workflow orchestration

• Experience designing applications that incorporate retrieval augmented generation, fine tuning, and structured prompting

• Experience with vector databases and retrieval systems such as Elasticsearch, OpenSearch, Pinecone, or Weaviate

• Experience with LLM evaluation, observability, and monitoring including latency, cost, accuracy, grounding, drift detection, and safety assessments

• Familiarity with ML lifecycle tools and processes such as feature stores, model registries, and CI or CD pipelines for AI services

• Familiarity with responsible AI principles, compliance, and governance processes related to AI systems in regulated environments

• Experience optimizing AI application performance including prompt efficiency, model selection, caching, batching, and cost management