Job Title : Forward Deployed Engineer (FDE) AI & Agent Engineering
Location: Morristown, NJ (Remote - But need to Travel once in a Month)
Key Responsibilities
Business Discovery & Solution Design
- Partner with business leaders, product owners, and operational teams to identify high-value AI use cases.
- Conduct workshops and discovery sessions to understand workflows, pain points, and business objectives.
- Translate business requirements into scalable AI and automation solutions.
- Define MVP scope, success criteria, KPIs, and implementation roadmaps.
AI Engineering & Development
- Design, build, and deploy Generative AI and Agentic AI solutions.
- Develop RAG (Retrieval Augmented Generation) applications leveraging enterprise knowledge sources.
- Build intelligent agents capable of automating underwriting, claims, customer service, IT support, and operational workflows.
- Integrate AI services with enterprise platforms, APIs, databases, SharePoint, ServiceNow, CRM, and document repositories.
Platform Integration & Deployment
- Deploy AI models and applications into Azure cloud environments.
- Build secure and compliant integrations aligned with enterprise governance standards.
- Configure monitoring, observability, logging, and performance metrics.
- Support production deployment and operational readiness activities.
Production Ownership
- Own the end-to-end success of deployed AI solutions.
- Troubleshoot production issues and optimize model performance.
- Improve solution accuracy, latency, scalability, reliability, and cost efficiency.
- Establish feedback mechanisms and continuous improvement processes.
Stakeholder Engagement
- Collaborate with business executives, architects, developers, data engineers, and security teams.
- Present solution architectures, progress updates, and business value realization metrics.
- Facilitate adoption and change management activities.
- Mentor internal teams on AI engineering best practices.
Innovation & Value Creation
- Continuously identify new AI opportunities within underwriting, claims, risk management, customer service, and corporate operations.
- Prototype emerging AI capabilities and demonstrate proof-of-value.
- Recommend reusable AI assets, frameworks, and accelerators.
- Support strategic AI roadmap development and future-state architecture.
Required Qualifications
Technical Skills
- Strong proficiency in Python and modern software engineering practices.
- Hands-on experience with Generative AI technologies, LLMs, and AI agents.
- Experience building RAG pipelines using vector databases and enterprise content repositories.
- Strong knowledge of Azure AI services, Azure OpenAI, Azure Functions, and cloud-native development.
- Experience with REST APIs, microservices, containers, and CI/CD pipelines.
- Familiarity with model deployment, monitoring, evaluation frameworks, and MLOps practices.
AI & Agent Frameworks
Experience with one or more:
- LangChain
- LangGraph
- Semantic Kernel
- AutoGen
- CrewAI
- Prompt Engineering and Evaluation Frameworks
- Vector Databases (Pinecone, Azure AI Search, Weaviate, ChromaDB)