ED
AI Architect
Edmo·Design
DesignPuneHybrid7 to 9 yrsVia Wellfound
Growth Marketing ManagerBI AnalystHR AnalystSupply Chain AnalystCompliance AnalystInvestment Analyst
Edmo·Design
Category
Design
Work mode
Hybrid
Type
Full Time
Experience
7 To 9 Yrs
Location
Pune
EDMO is an AI-powered company that provides enrollment-centric solutions to universities, colleges, and higher education institutions. By streamlining repetitive tasks—such as document verification, transcript evaluation, SOP/essay reviews, and applicant matching—EDMO enables its clients to process student applications faster and more accurately. Its intelligent workflows not only reduce administrative workload but also empower admission advisors to focus on personalized guidance and student engagement. With features like AI-powered chatbots, Photo ID verification, GPA calculator, and transfer credit evaluation, EDMO ensures transparency and efficiency across the enrollment journey. Institutions using EDMO services report significant time savings, improved decision-making, and enhanced student satisfaction. At its core, EDMO is built to reimagine & streamline admissions—making them smarter, quicker, and more human-centric.
As the Agentic AI Architect at EDMO, you will own the end-to-end technical design and architecture of our agentic AI systems. You will be the bridge between research-grade AI ideas and production-hardened implementations — defining how LLM pipelines, multi-agent orchestration, memory systems, and tool-use come together into a coherent, scalable platform. This is not a research or prototyping role. You will design systems that run at enterprise scale, handle real student interactions, integrate with university SIS/CRM platforms, and meet compliance standards (FERPA, SOC 2). Equally important, you will be able to communicate complex architecture decisions clearly to engineers, product stakeholders, and enterprise clients.
●Define the end-to-end agentic AI architecture — LLM orchestration layers, agent coordination mechanisms, memory management, tool-calling patterns, and multi-agent workflows ●Design multi-agent orchestration patterns including hierarchical agents, supervisor-worker topologies, plan-and-execute strategies, and agent-to-agent (A2A) communication ●Architect RAG (Retrieval-Augmented Generation) pipelines, hybrid search, and knowledge management systems tailored to higher-education content (catalogs, policies, student data) ●Establish architectural standards for prompt engineering, context-window management, token budgeting, and evaluation frameworks ●Design for non-functional requirements: latency targets, 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 Dev Sec Ops architecture and deployment patterns across multi-cloud environments. ●Implement human-in-the-loop (HITL) checkpoints for sensitive decision points within student journeys ●Establish monitoring, observability, and audit logging frameworks for compliance, traceability, and agent behavior analysis ●Design secure AI architectures — threat modeling, adversarial prompt defenses, and data privacy controls aligned with FERPA and SOC 2
●Produce clear architecture documentation: reference diagrams, integration patterns, decision records, ADRs, and runbooks for production operations ●Communicate architectural trade-offs to both engineering teams and non-technical enterprise clients in a structured, accessible way ●Lead architecture and design reviews, mentoring engineers on agentic patterns and production best practices ●Serve as the technical point of contact for enterprise client integrations — translating institutional requirements into AI system design
●Stay current with the latest agent frameworks (Lang Graph, Crew AI, Auto Gen, Google ADK), LLM advancements, and inference optimization techniques ●Build prototypes and proof-of-concepts to validate architectural approaches before committing to production builds ●Drive the technology roadmap for EDMO's agentic platform — identifying where autonomous agents can replace manual workflows with measurable ROI
●5+ years of hands-on software engineering, with 3+ years specifically in production AI/ML systems ●Demonstrated experience designing and shipping multi-agent AI systems in production (not just prototypes or demos) ●Deep expertise with LLM orchestration frameworks: Lang Chain, Lang Graph (preferred), and/or Auto Gen, Crew AI, Google ADK ●Strong command of Python and backend engineering fundamentals — APIs, microservices, async patterns ●Hands-on experience with RAG architectures, vector databases, and semantic search ●Proficiency with cloud platforms (AWS, GCP, or Azure) and containerized deployments (Docker, Kubernetes)
●Ability to design systems addressing latency, scalability, reliability, and cost simultaneously — not just "it works on my local machine" ●Experience with agent memory architectures: episodic, semantic, procedural — and state management in stateful multi-agent graphs ●Familiarity with LLM inference optimization — quantization, model routing, caching, context compression ●Understanding of API gateway design, service boundaries, versioning, and governance Communication & Leadership ●Ability to produce clear architecture diagrams and technical documentation accessible to both engineers and non-technical stakeholders ●Experience presenting architecture to enterprise clients or senior leadership ●Track record of leading technical design reviews and influencing architecture decisions without direct authority
●Tech Stack: Python, Lang Graph, Lang Chain, Google Gemini / Claude / Open AI (multi-LLM), Mongo DB, Databricks, Salesforce integrations, ●Deployment: Production-grade microservices, containerized on cloud with CI/CD pipelines ●Compliance Environment: FERPA, SOC 2, VPAT — security and privacy are first-class concerns ●Team: Small, high-caliber engineering team. Architects write architecture AND contribute to code ●Clients: US-based universities and Ed Tech platforms at enterprise scale
In 30 days: ●Full audit of existing agentic system architecture; documented gaps, risks, and improvement areas In 60 days: ●Delivered a reference agentic architecture for at least one production agent workflow; established architecture review process with the engineering team In 6 months: ●Led architecture for a major platform capability (e.g., multi-agent student advisor, autonomous enrollment workflow); communicated architecture to at least one enterprise client; established observability and evaluation framework for agents in production
●Level: Senior Architect ●Opportunity: Direct path to VP of
AI Architect at Edmo.
This opening is based in Pune (hybrid) and is listed as full time.
Category: Design.
Review the full listing on the source site for day-to-day responsibilities, required experience, and how to apply. Confirm the role is still open before you submit an application.