Discover
Understand customer problems, requirements and business processes.
ENTERPRISE AI ENGINEERING PROGRAM
Become a Forward Deployed AI Engineer
Build, deploy and optimize production-ready AI systems for real-world enterprise problems.
Master Python, FastAPI, LLMs, RAG, Agentic AI, cloud infrastructure, Docker, APIs and production deployment.
FDE / ENTERPRISE AI FLOW● LIVE
01BUSINESS
PROBLEM
PROBLEM
02AI
SOLUTION
SOLUTION
03BUILD &
INTEGRATE
INTEGRATE
04DEPLOY &
MONITOR
MONITOR
$ architect.enterprise_ai()
→ RAG pipeline initialized
→ Agent orchestration ready
→ Production deployment ready ✓
20Weeks Live Training
13Core Modules
2 YearsRecording Access
∞Enterprise Use Cases
01 / THE FDE MINDSET
More than AI.
Engineering that ships.
A Forward Deployed Engineer combines software engineering, AI and business problem-solving to build and deploy solutions for real enterprise requirements.
Engineer
Design and build secure, production-ready AI applications.
Deploy
Integrate, deploy, monitor and optimize enterprise AI systems.
02 / CAREER TRANSFORMATION
From engineer to FDE.
01Software Engineer
02Backend Engineer
03AI Engineer
04LLM Engineer
05RAG Engineer
06AI Agent Engineer
07Enterprise AI Engineer
08Forward Deployed Engineer
03 / TECHNOLOGY STACK
Learn what production teams use.
LLMs & AI APIs
OpenAI · Gemini · Mistral · Claude · Llama · Qwen
Backend & Data Stores
FastAPI · PostgreSQL · MongoDB · Redis
Cloud & DevOps
Docker · GitHub Actions · AWS · Azure · GitHub
Agent Frameworks
LangGraph · CrewAI · OpenAI Agents SDK
AI Ops & Data Engineering
MLflow · PySpark · Databricks · LangFuse · LangSmith · Phoenix
04 / ENTERPRISE AI ARCHITECTURE
Think in
systems.
Connect business requirements to models, data, APIs, agents, infrastructure and production monitoring.
BUSINESS REQUIREMENTS→CUSTOMER OUTCOME
↓
LLMsRAGAI AGENTSTOOLS / APIs
↓
FASTAPIDATA STORESENTERPRISE INTEGRATIONS
↓
AWSAZUREDOCKERCI/CD
↓
MONITOROPTIMIZESECUREDEPLOY
05 / CURRICULUM
13 modules.
One complete journey.
Explore the full Forward Deployed Engineering program.
Understanding the FDE role
FDE vs Software Engineer, AI Engineer and Solutions Architect
Customer-first engineering mindset
Business outcome-driven solutioning
Enterprise AI lifecycle and project workflow
Hands-on: Convert business requirements into a solution architecture
Advanced Python programming
Object-Oriented Programming (OOP)
Asynchronous programming
Type hints and code quality
Logging and exception handling
Virtual environments and packaging
Unit testing and production coding standards
Hands-on: Build production-ready Python utilities
REST API fundamentals
FastAPI development
Authentication (OAuth & JWT)
API versioning and documentation
OpenAPI and Swagger
Async API development
Rate limiting and best practices
Hands-on: Develop a secure FastAPI backend
SQL and Advanced SQL
ETL and ELT concepts
Data pipelines
Pandas and PySpark
Delta Lake fundamentals
Databricks basics
Data validation techniques
Hands-on: Build an enterprise data pipeline
AWS fundamentals: IAM, S3, Lambda, API Gateway
Azure fundamentals: Storage, Functions, Key Vault, AI Services
Infrastructure basics
Cloud deployment concepts
Hands-on: Deploy backend services to the cloud
LLM architecture and fundamentals
Prompt engineering
Context windows and tokenization
Embeddings
Function calling
Structured outputs
Model selection and cost optimization
Overview of GPT, Claude, Gemini and Llama
Hands-on: Compare LLMs for enterprise use cases
RAG architecture
Document chunking strategies
Embeddings and vector databases
Metadata filtering
Hybrid search
Re-ranking techniques
Citation generation
Hallucination reduction
LangChain and LlamaIndex
Chroma, Pinecone, PGVector, Azure AI Search
Hands-on: Build an enterprise document assistant
AI agent fundamentals
Tool calling
Memory management
Planning and reasoning
Reflection techniques
Multi-agent systems
Agent orchestration
MCP and A2A protocols
Human-in-the-loop workflows
LangGraph
CrewAI
OpenAI Agents SDK
Amazon Bedrock Agents
Hands-on: Build a multi-agent enterprise assistant
Microsoft Graph API
SharePoint integration
Slack and Microsoft Teams integration
Jira and Confluence integration
Salesforce and SAP connectivity
ServiceNow integration
Databricks and Snowflake integration
Hands-on: Integrate AI with enterprise platforms
Docker and containerization
CI/CD fundamentals
GitHub Actions
Kubernetes basics
Monitoring and logging
Secrets management
Production deployment strategies
Hands-on: Deploy an end-to-end AI application
AI security fundamentals
Prompt injection attacks
AI guardrails
Role-Based Access Control (RBAC)
Data privacy and compliance
Responsible AI principles
AI governance
Observability
Cost management
Hands-on: Secure an enterprise AI solution
Customer discovery workshops
Requirements gathering
Business process mapping
Rapid prototyping
Technical consulting
Solution architecture design
Architecture communication
Stakeholder management
Technical proposal writing
Handling ambiguous requirements
Change management
Customer demos and presentations
Customer success strategies
Workshop: Convert a client problem into an AI solution proposal
Enterprise AI project planning
End-to-end solution design
Production-oriented implementation
Customer problem to AI solution proposal
Presentation and demonstration
06 / CAREER OUTCOMES
Where your skills can take you.
01Forward Deployed AI Engineer
02AI Engineer
03Applied AI Engineer
04Generative AI Engineer
05AI Solutions Engineer
06Enterprise AI Consultant
07AI Architect
08AI Infrastructure Engineer
07 / FAQ
Questions, answered.
Yes. Forward Deployed Masters can help organizations identify and develop AI engineering talent with practical skills in Generative AI, LLMs, RAG, AI Agents, Python, FastAPI, cloud technologies and enterprise AI application development.
No. You do not need prior professional experience in AI or machine learning. The program introduces key AI application patterns from the foundations. A basic understanding of Python, APIs, databases and general software development is recommended.
Yes. All classes are live and instructor-led, delivered online over five months (20 weeks). Class recordings are available for two years and are designed to supplement live sessions.
You will build practical expertise across the modern Enterprise AI engineering stack, including LLMs, RAG, multimodal Generative AI, vector databases, API integrations, AI agents, AIOps tools, automation and production deployment workflows.
The program focuses on practical, enterprise-oriented AI engineering rather than only theoretical concepts. It is designed around building and implementing AI solutions for real-world business environments.
You will develop practical skills in LLM workflows, Generative AI, Agentic AI automation, AI deployment, LLMOps and monitoring.
A Forward Deployed AI Engineer combines software engineering, AI and business problem-solving skills to build and deploy AI solutions for real-world enterprise requirements.
Yes. You will learn to design and implement AI agents and agentic workflows for practical business automation and enterprise applications.
Yes. The course covers Retrieval-Augmented Generation, embeddings, vector stores/databases, retrieval workflows and LLM integration.
Yes. You will gain practical exposure to APIs, cloud infrastructure, containers, deployment workflows, monitoring and production-oriented AI application development.
Yes. The program is designed for software developers, engineers, cloud professionals, data professionals and other technology professionals who want to build practical AI engineering skills.
The skills developed can be relevant to roles such as Forward Deployed AI Engineer, AI Engineer, Applied AI Engineer, Generative AI Engineer, AI Solutions Engineer and Enterprise AI Consultant.
The program emphasizes combining AI engineering with software development, enterprise integration, deployment, automation and business problem-solving rather than focusing only on AI theory.
The course can be suitable for professionals who want to transition into or strengthen their skills in AI engineering, Generative AI, Agentic AI, enterprise AI and forward deployed engineering.
The program content references Hyderabad, Bangalore, Pune, Chennai, Mumbai, Delhi, Noida, Gurgaon, Kolkata, Ahmedabad, Vizag, Vijayawada, USA, UK, Canada, Australia, Dubai/UAE, Saudi Arabia, Qatar, Singapore, Germany, Japan and other countries.
08 / START YOUR JOURNEY
Ready to build Enterprise AI?
Join Forward Deployed Masters in Hyderabad and build practical AI engineering skills through live, project-based training.
VISIT US
Forward Deployed Masters
1st Floor, Everest Block, Metro Station, 106/A, Satyam Theatre Rd, behind Ameerpet, Kumar Basti, Swathi Avenue, Ameerpet, Hyderabad, Telangana 500038
Mon–Sat | Contact for batch timings
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