DE&A - AIML - Deep Learning - Generative AI

Design and develop enterprise-grade Generative AI and Agentic AI solutions.
• Build AI-powered assistants, copilots, and intelligent workflow automation platforms.
• Implement and optimize: Large Language Models (LLMs), Retrieval Augmented Generation (RAG),
Multi-Agent Systems, Semantic Search architectures
• Develop AI orchestration frameworks for autonomous and collaborative AI agents.
• Build scalable AI pipelines and microservices using Python and modern AI frameworks.
• Design vector search and enterprise knowledge retrieval solutions.
• Fine-tune prompts, optimize inference performance, and improve AI response quality.
• Develop secure API integrations and event-driven AI architectures.
• Collaborate with product, architecture, security, and engineering teams.
• Ensure responsible AI governance, security, compliance, and observability standards.
• Support deployment, monitoring, and continuous improvement of AI systems in production
Experience building enterprise AI copilots and autonomous AI agent platforms.
• Background in Financial Services, Cards & Payments, Fraud & Disputes, or Customer Servicing
domains.
• Experience with conversational AI, intelligent automation, and enterprise search solutions.
• Exposure to highly regulated enterprise environments.
• Strong stakeholder communication and architecture leadership skills.
Tools & Technologies
AI & GenAI - OpenAI, Azure OpenAI, Anthropic Claude, Hugging Face, LangChain, LangGraph, LlamaIndex,
Transformers
AI/ML & NLP - Python, PyTorch, TensorFlow, Scikit-learn, NLP, Prompt Engineering, AI Agents, RAG
Pipelines
Vector & Search Technologies - Pinecone, Weaviate, FAISS, ChromaDB, Elasticsearch, OpenSearch
Cloud & DevOps - AWS, Azure, GCP, Docker, Kubernetes, Jenkins, GitHub Actions, Azure DevOps
Integration Technologies - REST APIs, Microservices, Kafka, JSON/XML, API Gateway
Monitoring & Observability - Splunk, Dynatrace, Prometheus, Grafan
5+ years of IT experience with strong expertise in AI/ML engineering.
• Deep hands-on expertise in: Generative AI & Large Language Models, Retrieval Augmented
Generation (RAG), Multi-Agent Systems & AI Orchestration, Semantic Search & Knowledge Retrieval,
NLP & Machine Learning
• Strong programming proficiency in: Python, AI/ML frameworks and libraries
• Experience with: LangChain, LangGraph, LlamaIndex, OpenAI/Azure OpenAI APIs, Hugging Face
ecosystem
• Strong understanding of: Prompt Engineering, AI Agents, Context Management, Embedding Models,
AI Evaluation Frameworks
• Hands-on experience with Vector Databases: Pinecone, Weaviate, ChromaDB, FAISS,
Elasticsearch/OpenSearch
• Experience building REST APIs and AI-powered microservices.
• Strong knowledge of cloud-native AI deployment patterns on AWS/Azure/GCP.
• Experience with Docker, Kubernetes, CI/CD, and MLOps practices.
• Familiarity with enterprise-scale secure AI implementation and governance frameworks.