Lead AI Engineer • Building & Scaling Production AI Agents • Multi-Agent Systems Architect

> Currently shipping AI systems that serve millions of customers across Europe. 12+ years in tech (8+ years Data Science, 3+ years Software Engineering). I also love teaching Data Science and helping developers build production-ready applications.

Lead AI Engineer at Deutsche Telekom Building, scaling, and governing AI Agents using Google's Agent Development Kit (ADK), Agent Builder, and Agent Engine.

• Live in Production: Serving millions of customers at telekom.de
• Handling 7,500+ concurrent sessions and 25,000+ questions daily—reducing human agent escalations by 40% while driving 20% year-over-year operational savings
• Multi-agent architecture answering complex customer support queries across Telekom's European markets
• Built with enterprise-grade reliability and governance

I build end-to-end AI agents and ship production systems that can be used immediately—which solve real problems and add value to the org/customer.

• AI Agents: Single-agent → Multi-agent → MCP-based → Browser agents → Voice agents → Local agents
• Agent Architectures: Crews, swarms, hierarchical planning, tool orchestration, memory management, eval frameworks
• RAG Systems: Simple chains → Agentic RAG → Hybrid search (BM25 + Cross-encoders) → Local RAG with Gemma/Llama
• Chat-With-Anything: GitHub, Gmail, PDFs, videos, research papers (production-grade parsing + retrieval)
• Fine-Tuning: Gemma, Llama, and OSS models using PEFT/LoRA/QLoRA for instruction tuning
• Production Systems: Conversation AI platforms with human-in-the-loop, monitoring, and governance

GPT-4/GPT-4o Llama3 Gemma LangChain LangGraph ADK DSPy HuggingFace Transformers RAG Prompt Engineering

MCP Agent Development Kit CrewAI AutoGen OpenAI SDK Function Calling Tool Use Agent Evaluation

PySpark SQL PostgreSQL pgvector Qdrant Neo4j Redis Milvus NumPy Pandas

Docker Kubernetes FastAPI MLflow Airflow ArgoCD AWS (SageMaker, ECS, ECR, S3) Azure OpenAI GitLab CI/CD DVC Argilla

Python PyTorch Keras Streamlit FastAPI Linux Git

Locust K6 JMeter

• Throughput Optimization: Designed systems handling 7,500+ concurrent sessions with optimized inference pipelines, batching strategies, and async processing to maximize requests/sec
• Latency Optimization: Sub-second responses via model quantization (GGUF/AWQ), efficient vector retrieval (HNSW), and Redis caching layers
• Load Testing at Scale: Distributed Locust clusters simulating 25,000+ daily queries to identify bottlenecks in agent orchestration and tool latency
• Production Profiling: GPU utilization tuning, memory leak detection, and auto-scaling strategies for peak traffic

• M.Sc. in Computer Science, University of Pune (2013)
• 12+ years IT experience: 8+ years as Data Scientist, 3 years as Software Engineer
• Specialized in Conversational AI and making AI applications production-ready at scale

I'm passionate about education and building the AI engineering community:

• Teaching AI/Agents/Classical ML/DL across top EdTech platforms
• Helping students and professionals upskill with hands-on, production-focused curriculum
• Sharing real-world patterns for Agent Dev, Multi-Agent teams, RAG, and LLMOps

• 💼 Portfolio: [Your Portfolio Link]
• ✉️ Email: swapnil89.desai@gmail.com
• 💡 Medium: [Your Medium Articles]
• 🏢 LinkedIn: [Your LinkedIn]
• 🐦 Other: [Twitter/X or other relevant]

Open to collaborating on: AI Agents, Multi-Agent Systems, RAG, Conversational AI, MLOps, and Production LLM Applications.

⚡ Avid reader in AI, programming, and system design. Committed to continuous learning and shipping code that actually works in production.