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Agentic AI Architect

EDMO

Pune

5-8 years

Today

$41.0K–60.2K/yr

Full time

Onsite

Skills Required

LLM orchestration

RAG

LangChain

Vector Database

LLM inference optimization

Google Gemini

Claude

OpenAI

LangGraph

AutoGen

CrewAI

Google ADK

Python semantic search

AWS

Description

EDMO is building conversational intelligence for higher education with production-grade agentic AI. This senior role owns end-to-end architecture for scalable, compliant, enterprise AI systems.

Company: EDMO

Role: Agentic AI Architect

Location: Pune

Experience

- 5+ years of hands-on software engineering
- 3+ years specifically in production AI/ML systems
- Demonstrated experience designing and shipping multi-agent AI systems in production
- Experience with cloud platforms: AWS, GCP, or Azure
- Experience with containerized deployments: Docker, Kubernetes

Responsibilities

- Own the end-to-end technical design and architecture of agentic AI systems
- Bridge research-grade AI ideas and production-hardened implementations
- Define LLM pipelines, multi-agent orchestration, memory systems, and tool-use
- Design multi-agent orchestration patterns including hierarchical agents, supervisor-worker topologies, plan-and-execute strategies, and agent-to-agent communication
- Architect RAG pipelines, hybrid search, and knowledge management systems for higher-education content
- Establish standards for prompt engineering, context-window management, token budgeting, and evaluation frameworks
- Design for latency, throughput, reliability, observability, cost controls, and scaling guardrails
- Build production-grade systems with structured error handling, retry logic, circuit breakers, and fallback execution paths
- Define DevSecOps architecture and deployment patterns across multi-cloud environments




- Implement human-in-the-loop checkpoints for sensitive decision points in student journeys
- Establish monitoring, observability, and audit logging frameworks for compliance, traceability, and agent behavior analysis
- Design secure AI architectures aligned with FERPA and SOC 2
- Produce architecture documentation including reference diagrams, integration patterns, decision records, ADRs, and runbooks
- Communicate architectural trade-offs to engineers, product stakeholders, and enterprise clients
- Lead architecture and design reviews and mentor engineers on agentic patterns and production best practices
- Serve as the technical point of
- Stay current with agent frameworks, LLM advancements, and inference optimization techniques
- Build prototypes and proof-of-concepts to validate architectural approaches
- Drive the technology roadmap for the agentic platform and identify automation opportunities with measurable ROI

Additional Responsibilities

- Work with universities and EdTech institutions at enterprise scale
- Integrate with university SIS and CRM platforms
- Handle real student interactions in production
- Full audit of existing agentic system architecture in 30 days
- Deliver a reference agentic architecture for at least one production agent workflow in 60 days
- Establish an architecture review process with the engineering team in 60 days
- Lead architecture for a major platform capability within 6 months
- Communicate architecture to at least one enterprise client within 6 months




- Establish observability and evaluation framework for agents in production within 6 months
- Contribute to code as part of a small, high-caliber engineering team

Nice To Have

- Experience with voice AI / telephony
- Salesforce / CRM integration experience
- Higher education domain knowledge
- FERPA / SOC 2 compliance experience
- Familiarity with n8n or workflow automation tools
- Experience with Databricks / MongoDB for AI data pipelines
- Google Gemini / Vertex AI experience

More Skills multi-agent orchestration, microservices, async patterns, agent memory architectures, episodic memory, semantic memory, procedural memory, state management, quantization, model routing, caching, context compression, API gateway design, service boundaries, versioning, governance, threat modeling, adversarial prompt defenses, data privacy controls, monitoring, observability, audit logging, DevSecOps, multi-cloud environments, GCP, Azure, Docker, Kubernetes, MongoDB, Databricks, Salesforce integrations, VPAT

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