Experience
12 - 15 yrs
Job Location
Bengaluru, India
Vacancy
1
Designation
Platform Architect
Job Type
ONSITE
Job Description
As an AI Platform Architect, you will design and scale enterprise-grade Agentic AI and Generative AI platforms that power copilots, autonomous workflows, and multi-agent systems. This is a hands-on architect role for a builder who combines deep distributed-systems thinking with practical expertise in LLMs, agent orchestration, and cloud-native platforms.
You will define reference architectures, engineering standards, and core platform capabilities that enable teams to build, deploy, and operate AI systems at scale.
Key Responsibilities
- Architect scalable Agentic AI platforms supporting multi-agent orchestration, tool usage, memory, planning, and reasoning workflows
- Design end-to-end GenAI platforms, including:
- Prompt orchestration
- Retrieval-Augmented Generation (RAG) pipelines
- Vector databases
- LLM integrations
- Define modular, microservices-based, API-first architectures enabling rapid development of AI copilots and autonomous systems
- Agentic GenAI Systems
- Define architectural patterns for:
- Agent orchestration and coordination
- Planning, reflection, and reasoning loops
- Human-in-the-loop and feedback-driven systems
- Define architectural patterns for:
- Evaluate and integrate emerging frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, and related ecosystems into enterprise platforms
- Production Readiness Reliability
- Ensure production-grade reliability across AI platforms, including:
- Observability and monitoring
- Evaluation and experimentation frameworks
- Guardrails, safety, and governance
- Cost optimization for LLM-based systems
- Ensure production-grade reliability across AI platforms, including:
- Lead architecture across LLMOps, MLOps, and platform operations
- Cloud, DevOps Infrastructure
- Drive cloud-native platform architecture using AWS, Azure, or GCP
- Lead Kubernetes-based deployments, CI/CD pipelines, and Infrastructure as Code (IaC)
- Ensure scalability, security, and resilience of AI workloads
- Collaboration Technical Leadership
- Partner with data science, product, and business teams to translate AI use cases into robust platform capabilities
- Mentor senior engineers and architects; set engineering standards, reference architectures, and best practices
- Act as a technical thought leader for enterprise AI platform strategy
Required Skills Experience
- 12 15 years of experience in platform engineering / architecture , with strong depth in distributed systems
- Deep expertise in cloud platforms (AWS / Azure / GCP) and Kubernetes-based architectures
- Hands-on experience with LLMs, RAG architectures, and vector databases (e.g., Pinecone, FAISS, Weaviate)
- Strong understanding of agentic frameworks, multi-agent systems, and orchestration patterns
- Experience across LLMOps / MLOps , including:
- Model deployment
- Monitoring and evaluation
- Lifecycle and version management
- Proficiency in microservices, APIs, event-driven systems , and scalable backend engineering
- Strong coding experience in Python / Java / Go , with system-design depth
- Experience working with data platforms (real-time + batch, large-scale data processing)
- Solid understanding of AI safety, governance, and responsible AI frameworks
- Good to Have
- Experience building enterprise AI copilots or autonomous workflows
- Exposure to reasoning frameworks, chain-of-thought orchestration , and agent memory systems
- Prior consulting or client-facing experience leading AI-driven transformation
No Referrers Available
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