Forward Deployement Engineer

Role overview

Forward Deployement Engineer at Fulcrum Digital

Business Discovery & Solution Design Partner with business leaders, product owners, and operational teams to identify high-value AI use cases.

Responsibilities

• 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)

Employment details

• Location: Haveli [Maharashtra] [India]