Forward Deployement Engineer

Fulcrum Digital Inc; Pune District; On-site; INR 1,500,000 - 3,500,000; Full time

Job summary

Fulcrum Digital Inc. is seeking an AI Engineering lead to partner with business leaders and deliver scalable AI and automation solutions. You will design, build, and deploy Generative AI and agent-based systems, leveraging enterprise data sources and modern cloud services.

You will define MVPs, KPIs, and roadmaps, and own production deployments, monitoring, and continuous improvement of AI solutions across underwriting, claims, and customer service workflows.

Qualifications

• 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.

Responsibilities

• 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.
• 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.

Skills

Python

Software engineering practices

Generative AI

LLMs

AI agents

RAG pipelines

Vector databases

Azure AI services

Azure OpenAI

Azure Functions

Cloud-native development

REST APIs

Microservices

Containers

CI/CD

MLOps

Tools

LangChain

LangGraph

Semantic Kernel

AutoGen

CrewAI

Prompt Engineering & Evaluation Frameworks

Pinecone

Azure AI Search

Weaviate

ChromaDB

Job description

• 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.
  
• 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.
  

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)