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Job Description
Senior AI Platform Engineer / Senior Full Stack Developer
Python / FastAPI / AI / LLM / MCP / Full Stack / DevOps
About the Role
We are hiring a Senior AI Platform Engineer / Senior Full Stack Developer for our team in Gurugram, Haryana.
This is a full-time, onsite role for candidates with minimum 5+ years of experience.
The candidate will work directly under the CEO and will be responsible for building end-to-end AI-powered platforms across backend, frontend, AI/LLM integrations, MCP integrations, workflow automation, DevOps, cloud deployment, and production system architecture.
This is not a narrow backend-only or frontend-only role. We need someone who can independently design, build, deploy, and scale complete AI-native products.
The ideal candidate should be capable of building systems that work through chat, documents, files, voice, video, images, dashboards, approvals, enterprise tools, APIs, workflows, and automation layers.
What You Will Build
You will help build AI systems that can:
Generate proposals, PPTs, PDFs, reports, contracts, invoices, RFQs, course materials, and business documents
Understand and process PDFs, Word files, Excel sheets, CSVs, decks, images, audio, video, and structured data
Build chat-first AI workflows for users, admins, customers, and internal teams
Search, retrieve, compare, summarize, and reason across knowledge bases and uploaded files
Integrate LLMs, AI/ML models, RAG pipelines, vector databases, MCP servers, and multimodal AI systems
Connect AI agents with external tools, APIs, databases, files, workflows, and business systems
Build workflow engines with tasks, approvals, reminders, status tracking, audit logs, and human-in-the-loop controls
Manage long-running AI jobs using queues, workers, retries, progress tracking, and background processing
Support real-time systems using WebSockets, streaming, queues, and event-driven architecture
Deploy systems reliably using Docker, Kubernetes, CI/CD, cloud platforms, and scalable infrastructure
Key Responsibilities
Full Stack Product Development
Design, develop, and manage complete full stack applications
Build scalable backend systems using Python and FastAPI
Develop responsive frontend applications using HTML, CSS, Angular, React, or Next.js
Build clean dashboards, admin panels, chat interfaces, file preview screens, workflow screens, and approval panels
Convert business requirements into working AI products
Take complete ownership from architecture to deployment
Backend Engineering
Build secure, scalable, and production-ready REST APIs
Design service architecture for AI-native applications
Implement authentication and security using JWT, OAuth2, RBAC, and permission-based access
Work with PostgreSQL, MySQL, MongoDB, and structured data stores
Build async APIs, background jobs, queues, scheduled tasks, and retry systems
Create logging, monitoring, error handling, and status-tracking systems
Optimize systems for performance, scalability, and reliability
AI / LLM / RAG Development
Integrate AI/ML models and LLMs into real-world applications
Work with LLMs such as GPT, LLaMA, Claude, Gemini, open-source models, or self-hosted models
Build RAG pipelines using embeddings, vector databases, and retrieval systems
Work with vector databases such as FAISS, Pinecone, Chroma, Weaviate, or similar
Create prompt orchestration and tool-calling workflows
Build AI systems that can reason over documents, structured data, business context, and user instructions
Develop AI agents that can generate, validate, modify, and improve outputs
Build AI systems that support chat-based execution and human approval before final action
MCP Integration & Agentic AI Systems
Build and integrate MCP-based systems for connecting AI agents with external tools and business workflows
Develop MCP servers and MCP clients for secure tool access
Enable LLMs and AI agents to interact with:
APIs
Databases
Files
CRMs
Email systems
Calendar systems
Document repositories
Workflow systems
Reporting tools
Internal enterprise platforms
Build controlled AI actions such as:
Reading documents
Searching knowledge bases
Generating reports
Updating workflows
Calling APIs
Creating tasks
Triggering automations
Fetching business data
Preparing documents for approval
Implement safe tool-calling workflows with:
Permissions
User approvals
Role-based access
Audit logs
Action history
Error handling
Security controls
Ensure MCP and agent integrations are secure, scalable, auditable, and production-ready
Document, File & Multimodal Intelligence
Build pipelines to ingest, parse, and understand:
PDFs
Word documents
PowerPoint decks
Excel files
CSV files
Images
Audio
Video
Screenshots
Structured and unstructured data
Implement OCR, transcription, parsing, classification, extraction, summarization, and content generation workflows
Build systems that can generate:
PPTs
PDFs
Reports
Contracts
Invoices
Proposals
RFQs
Course materials
Scripts
Assessments
Business summaries
Support editable AI-generated assets and regeneration based on user feedback
Maintain consistency across generated documents, slides, reports, and workflows
Workflow Automation
Build workflow engines for tasks, approvals, reminders, status tracking, and execution monitoring
Create human-in-the-loop approval systems before sending emails, proposals, documents, or business actions
Build admin notification systems and complete interaction history tracking
Support chat-based workflow updates such as:
“Generate proposal”
“Send RFQ to vendor”
“Show pending approvals”
“Mark this task complete”
“Summarize this document”
“Create invoice”
“Prepare PPT”
“Send for approval”
Maintain audit-friendly logs for all actions, user decisions, AI outputs, and system changes
DevOps, Cloud & Deployment
Containerize applications using Docker
Deploy and manage services using Kubernetes
Set up CI/CD pipelines using GitHub Actions, Jenkins, or GitLab CI
Work with cloud platforms such as AWS, Azure, or GCP
Implement load balancing, scaling, monitoring, logging, and uptime management
Manage local-first and cloud-supported deployment environments
Build secure and reliable deployment pipelines
Optimize infrastructure for cost, speed, reliability, and maintainability
Must-Have Skills
Experience
Minimum 5+ years of full stack development experience
Strong experience building production-grade software systems
Ability to independently design, build, test, deploy, and scale applications
Experience working in fast-paced, high-ownership environments
Backend
Advanced Python programming
Hands-on experience with FastAPI
Strong understanding of REST APIs and backend architecture
Async programming and performance optimization
Background jobs, queues, workers, retries, and scheduled tasks
Authentication, authorization, and secure API development
Strong system design and debugging skills
Frontend
Strong frontend development experience
Experience with HTML, CSS, Angular
React / Next.js experience will be preferred
Ability to build clean, responsive, and user-friendly interfaces
Experience building:
Dashboards
Chat interfaces
Admin panels
File viewers
Approval screens
Workflow tracking screens
Databases
PostgreSQL / MySQL / MongoDB
Schema design and query optimization
Structured data handling
Event logs, user logs, task logs, workflow state, and audit history
Experience designing scalable database models for business applications
AI / LLM Skills
Strong understanding of Artificial Intelligence and Machine Learning concepts
Hands-on experience building AI/LLM-powered applications
Experience with:
Prompt engineering
RAG
Embeddings
Vector databases
AI agents
Tool calling
MCP integration
Document intelligence
Multimodal AI workflows
AI workflow orchestration
Ability to integrate AI models into real-world production systems
Ability to build AI systems that are reliable, explainable, and user-controlled
MCP / Agent Integration
Experience with MCP or similar tool-integration frameworks
Ability to connect LLMs with APIs, databases, files, tools, and enterprise systems
Understanding of agent orchestration, tool permissions, context management, and workflow automation
Ability to build safe and auditable AI actions
Knowledge of function calling, structured outputs, and agent-based workflows
DevOps & Cloud
Docker experience is mandatory
Kubernetes experience is highly preferred
CI/CD pipeline setup
AWS / Azure / GCP deployment experience
Understanding of:
Microservices
Load balancing
Scaling
Monitoring
Logging
Infrastructure reliability
Preferred Skills
FastAPI, Django, Flask
React, Next.js, Angular
LangChain, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, or similar frameworks
MCP server/client development
Agentic AI workflows
Tool-calling and function-calling systems
FAISS, Pinecone, Chroma, Weaviate
Celery, Redis, RabbitMQ, Kafka, or similar queue systems
WebSockets and real-time streaming
OCR, speech-to-text, transcription, and media-processing pipelines
PDF, PPT, Excel, and report generation libraries
Self-hosted or local LLM deployment
Role-based access control and audit logging
AI-generated code validation and execution workflows
Workflow engines with approval loops
Experience with multimodal AI systems
Example Systems You May Work On
AI Sales & Proposal Management System
AI RFQ Automation System
AI Accounting & Document Management System
AI Email & Communication Manager
AI Inventory Management System
AI Attendance & Activity Monitoring System
Voice Identity & Interaction Profiling System
Course Material & Video Generation Platform
AI Knowledge Retrieval Platform
AI Document Intelligence System
AI Workflow Automation Platform
AI Agent Platform with MCP Integrations
Ideal Candidate
We are looking for someone who:
Thinks like a product builder, not just a coder
Can convert unclear business requirements into working software
Can build backend, frontend, AI workflows, MCP integrations, and deployment pipelines end to end
Has strong architecture and problem-solving ability
Can work directly with leadership and take ownership
Is comfortable in a fast-paced, high-pressure environment
Understands both engineering depth and user workflow design
Click on Apply to know more.