Agentic AI & Multi-Agent Systems ArchitectFrom toy API wrappers to production autonomous agent swarms.
Master cyclic state machines, LangGraph architectures, multi-agent supervisor swarms, vLLM inference optimization, and automated evaluation loops (Ragas). Defend your designs at the Staff/Principal level.
- Duration
- 10 weeks
- Cadence
- 10 live 1:1 sessions + architecture blueprints + interview loops
- Who it's for
- Senior Engineers transitioning to Staff AI Engineer or AI Architect
- Mentor
- Ashwin Agrawal, every session
₹39,999
One-time. Full 10-week 1:1 flagship accelerator directly with Ashwin.
How Agentic AI & Multi-Agent Systems Architect is run
Every session is 1:1 and live. Between sessions the agent holds your roadmap, answers the in-between questions, and escalates anything that needs Ashwin.
Production LangGraph state machines with time-travel & human-in-the-loop
High-throughput inference with vLLM, PagedAttention, and AWQ quantization
Automated evaluation loops (Ragas, DeepEval) & synthetic red-teaming
Executive 1:1 mentoring with Director of Data Science & AI Ashwin Agrawal
The phases, in order
A starting structure, not a syllabus you're locked into — the agent tailors it to your situation in the first conversation, and Ashwin adjusts it as you go.
Weeks 1–2
LangGraph Core & Cyclic State Machines
- StateGraph, cyclic graphs, and state reducers vs standard DAGs
- Dynamic checkpointing, time-travel debugging, and human-in-the-loop breakpoints
- Cycle termination guards, infinite loop prevention, and tool retry mechanisms
Weeks 3–4
Multi-Agent Swarms & Consensus Protocols
- Hierarchical supervisor pattern, debate protocols, and consensus voting
- Inter-agent messaging protocols and shared state synchronization
- Integrating external tools via Model Context Protocol (MCP)
Weeks 5–6
vLLM, TensorRT-LLM & Sub-Second Serving
- PagedAttention memory management and KV cache fragmentation elimination
- Continuous dynamic iteration-level batching for 4x throughput gains
- AWQ 4-bit quantization and multi-LoRA concurrent serving clusters
Weeks 7–8
Observability, Evals & Red-Teaming
- Automated evaluation with Ragas, DeepEval, and LLM-as-a-judge calibration
- Production latency tracing & span waterfalls with Langfuse / OpenTelemetry
- Adversarial prompt injection testing, jailbreak defense, and NeMo guardrails
Weeks 9–10
Staff System Design Loops & Offer Close
- Staff / Principal AI architecture whiteboard rounds (Google/Meta/OpenAI bar)
- Handling non-deterministic failure modes and cost-per-token trade-offs
- Multi-offer compensation leverage and stock grant negotiation (₹40L–₹1.15 Cr)
What you leave with
- 01
Production multi-agent swarm repository capable of self-healing and tool execution
- 02
Deep architectural defense of non-deterministic systems in Staff loops
- 03
Elite compensation positioning for ₹40 LPA to ₹1.15 Cr offers
- 04
Direct executive referrals into Tier-1 AI labs and unicorns
Nobody joins Agentic AI & Multi-Agent Systems Architect without the free class first
Fifteen focused minutes. You share where your career or job search is stuck; Ashwin names the key bottleneck and your next two moves. No card, no pitch.
- An honest diagnostic of where your applications or interviews are breaking down
- One concrete high-impact action you can take immediately
- A straight answer on the optimal roadmap for your target salary band
Not quite the right fit?
The agent will tell you which one matches — and it's happy to say none of them do yet.