YES MADAM — AI Lead
Location: Sector 63, Noida
Experience: 12+ Years
Employment Type: Full-Time
Work Mode: Work From Office
Team: Engineering / Technology
About the Role
YES MADAM is looking for an experienced AI Lead to lead the architecture, development, and adoption of AI/GenAI solutions across the organization.
The ideal candidate should combine strong software architecture and backend engineering expertise in Java and Python with hands-on experience in Generative AI, LLMs, RAG, AI Agents, and scalable AI systems.
The role involves working closely with Engineering, Product, Data, and Technology leadership to identify high-impact AI opportunities and convert them into secure, scalable, reliable, production-ready solutions.
Key Responsibilities
- Own the organization's AI/GenAI technology strategy and architecture.
- Design and lead scalable AI-powered applications and platforms.
- Build production-grade solutions using Python and Java.
- Lead development of LLM applications, RAG pipelines, AI Agents, and intelligent automation.
- Evaluate and integrate LLM platforms such as OpenAI, Google Gemini, AWS Bedrock, and other relevant models.
- Design architectures involving Vector Databases, Embeddings, Semantic Search, and RAG.
- Drive decisions around AI frameworks, model integration, orchestration, evaluation, and deployment.
- Integrate AI capabilities with existing Java/Spring Boot microservices and backend platforms.
- Define engineering best practices for prompt engineering, model evaluation, security, testing, observability, and responsible AI.
- Lead technical POCs and convert successful experiments into production-ready solutions.
- Identify and prioritize high-impact AI use cases with Product, Engineering, Data, and Business teams.
- Establish standards for code quality, scalability, reliability, security, performance, and observability.
- Mentor and guide AI/ML and backend engineering teams.
- Stay updated with GenAI, LLMs, Agentic AI, AI infrastructure, and developer tooling.
- Own the technical roadmap and contribute to broader technology strategy and architecture decisions.
Technical Skills1. Backend & Programming
Must Have:
- Strong hands-on experience with Java and Python
- Strong expertise in:
- Java
- Spring Boot
- REST APIs
- Microservices
- Strong understanding of:
- OOP
- Distributed Systems
- Scalable Backend Architecture
- System Design
- Experience building high-performance, production-grade applications
2. AI / Generative AI
Must Have:
- Hands-on experience with Generative AI
- Experience building LLM-based applications
- Strong understanding of:
- LLMs
- RAG
- Prompt Engineering
- LLM Orchestration
- Experience building AI Agents / Agentic AI systems
- Experience integrating LLM APIs and models
- Experience with:
- Embeddings
- Semantic Search
- Vector Databases
- Understanding of AI application evaluation, monitoring, and optimization
- Experience taking AI solutions from POC Production
3. AI Technologies
Experience with one or more:
- OpenAI / GPT APIs
- Google Gemini
- AWS Bedrock
- LangChain
- LangGraph
- LangChain4j
- Spring AI
- Pinecone
- Qdrant
- Milvus
- Weaviate
- AI/ML APIs
- Model-serving platforms
Architecture & Leadership
The candidate should have strong expertise in:
- System Design
- Solution Architecture
- Distributed Systems
- Scalable Architecture
- Technical Leadership
- Architecture Ownership
- Technology Roadmaps
- Engineering Strategy
- Cross-functional Team Leadership
- Stakeholder Management
- Mentoring
- Business-to-Technology Translation
- Problem Solving & Decision Making
Candidate ProfileMust Have
- 12+ years overall software engineering experience
- Strong professional experience with both Java and Python
- Strong hands-on AI/GenAI experience
- Experience with LLMs, RAG, and AI Agents
- Experience designing AI application architecture
- Proven experience taking AI solutions from POC to Production
- Strong Java + Spring Boot + Microservices background
- Strong System Design / Solution Architecture expertise
- Experience with Cloud and Distributed Systems
- Technical leadership and architecture ownership
- Strong communication and stakeholder-management skills
Preferred
- High-scale / consumer-facing technology experience
- Product company / startup experience
- Experience building AI products used by large user bases
- Strong AWS experience
- MLOps / LLMOps exposure
- Kubernetes
- Docker
- CI/CD
- Observability
- AI evaluation frameworks
- Model monitoring
Domain Bonus
Exposure to:
- Recommendation Systems
- Personalization
- Conversational AI
- Intelligent Automation
Key Success Metrics
The AI Lead will be measured on:
- Successful delivery of production-ready AI/GenAI solutions
- Adoption of AI capabilities across business and technology platforms
- Improvement in engineering productivity through AI
- Scalable, secure, and reliable AI architecture
- Successful conversion of POCs into production
- Development and growth of the AI engineering team
- Measurable business impact from AI initiatives
