AI Architect

Tachyon Technologies; Hyderabad; On-site; INR 4,500,000 - 7,000,000; Full time

Job summary

Tachyon Technologies in Hyderabad is seeking a Senior AI Architect to own enterprise AI transformation end to end, from design to production at scale. You will define standards, build reusable components, and drive AI delivery across platforms.

The role requires extensive cloud architecture background, hands-on GenAI/Agentic experience, and the ability to lead workshops, guide engineers, and shape architecture practices within a high-impact enterprise environment.

Qualifications

• 15+ years in software/enterprise/cloud architecture.
• A production GenAI/Agentic system you architected and shipped.
• Deep cloud architecture experience on Azure/AWS/GCP.
• Proficiency with AI frameworks (LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI).
• Strong Python programming ability and review of implementation details.
• Experience with microservices and enterprise integration patterns.

Responsibilities

• Architect end-to-end enterprise AI solutions across applications, APIs, data, and cloud infrastructure.
• Design and lead Generative AI and Agentic AI solutions using LLMs, RAG, tool calling, and multi-agent orchestration.
• Define cloud-native architectures for AI workloads across Azure/AWS/GCP with managed services, containers, Kubernetes, and serverless patterns.
• Evaluate models, frameworks, vector databases, and cloud services against security, performance and cost.
• Design integrations between AI solutions and Salesforce, SAP, ServiceNow, ERP/CRM, data platforms, and external APIs.
• Create architecture blueprints, reference patterns, reusable components, and technical standards.
• Lead architecture workshops, design reviews, and PoCs with engineering and customer teams.
• Define AI evaluation and observability: grounding, accuracy, latency, cost, safety.
• Establish guardrails, human-in-the-loop controls, identity models, and Responsible AI practices.
• Mentor senior engineers and build architecture practice across AI initiatives.

Skills

Years of experience

GenAI/Agentic AI

Cloud architecture

LangChain/LangGraph

Python programming

REST APIs/microservices

Enterprise AI knowledge

Communication

Education

Cloud architecture certification

Tools

Azure/GCP/AWS knowledge

Job description

Enterprise AI | Generative AI | Agentic AI | Cloud Architecture | Hyderabad

Generative AI and agentic systems are moving from pilots to the core of how enterprises operate — and Tachyon Technologies is where that shift is being architected. We're looking for a senior AI Architect who wants to own that transformation end to end: designing the systems, setting the standards, and seeing solutions run in production at enterprise scale, not just in a slide deck.

This is a role for someone who has already done real cloud architecture, has since built genuine depth in LLMs, RAG, and agentic design, and wants a platform where that combination is the whole job — not a side project bolted onto something else.

AI Architect

Enterprise AI | Generative AI | Agentic AI | Cloud Architecture | Hyderabad

Generative AI and agentic systems are moving from pilots to the core of how enterprises operate — and Tachyon Technologies is where that shift is being architected. We're looking for a senior AI Architect who wants to own that transformation end to end: designing the systems, setting the standards, and seeing solutions run in production at enterprise scale, not just in a slide deck.

This is a role for someone who has already done real cloud architecture, has since built genuine depth in LLMs, RAG, and agentic design, and wants a platform where that combination is the whole job — not a side project bolted onto something else.

What You Will Do

• Architect end-to-end enterprise AI solutions spanning applications, APIs, data, cloud infrastructure, security, integrations, and user experience.
• Design and lead Generative AI and Agentic AI solutions using LLMs, RAG, enterprise search, tool/function calling, and multi-agent orchestration.
• Define cloud-native architectures for AI workloads on Azure, AWS, and/or GCP using managed AI services, containers, Kubernetes, and serverless patterns.
• Evaluate and select models, frameworks, vector databases, and cloud services against business, security, performance, and cost requirements.
• Design integrations between AI solutions and enterprise platforms — Salesforce, SAP, ServiceNow, ERP/CRM, data platforms, and external APIs.
• Create architecture blueprints, reference patterns, reusable components, and technical standards for AI delivery.
• Lead technical discovery, architecture workshops, design reviews, and proof-of-concept initiatives with engineering and customer teams.
• Define AI evaluation and observability approaches — grounding, accuracy, hallucination risk, latency, cost, and safety.
• Establish guardrails, human-in-the-loop controls, identity and access models, and Responsible AI practices.
• Mentor senior engineers and technical leads, and help build strong architecture practice across AI initiatives.

What You Bring

• 15+ years in software engineering, solution architecture, enterprise architecture, or cloud architecture, with recent hands-on technical work.
• A production GenAI or Agentic AI system you've personally architected and shipped — not a POC — using LLMs, RAG, tool/function calling, or multi-agent orchestration.
• Deep, hands‑on cloud architecture experience on Azure, AWS, or GCP; multi‑cloud experience is a strong plus.
• Working fluency with modern AI frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or CrewAI.
• Strong software engineering foundation with hands‑on programming, preferably Python, and the ability to review implementation‑level decisions.
• Solid grounding in microservices, REST APIs, event‑driven architecture, and enterprise integration patterns.
• Experience with relational, NoSQL, and vector data platforms, and designing data/knowledge access patterns for AI.
• Excellent communication — equally comfortable with engineering teams and business/technology leaders.

Also Great to Have

• Infrastructure-as-Code (Terraform, Bicep, CloudFormation), CI/CD, and production support practices.
• Hands‑on exposure to Azure OpenAI/AI Foundry, AWS Bedrock, or Google Vertex AI/Gemini.
• Cloud architecture certification from Azure, AWS, or GCP.
• Experience building reusable AI platforms, accelerators, or enterprise AI capabilities.
• Exposure to Model Context Protocol (MCP), knowledge graphs, or advanced enterprise search.
• Background in customer-facing architecture, solutioning, or technical consulting.

Why Tachyon

• Own architecture decisions on high‑visibility enterprise AI programs, from first workshop to production rollout.
• Work at the intersection of deep cloud engineering and cutting‑edge agentic AI — not one at the expense of the other.
• Shape reusable patterns and standards that other architects and engineers will build on.
• Direct exposure to customer stakeholders and technology leadership, with real influence over technical direction.