AI Platform Architect: Agentic & Generative AI - Cogentiq
Fractal Analytics4 months ago
Bengaluru, IndiaStaff+
Responsibilities
- Architect scalable agentic AI platforms supporting multi-agent orchestration, tool usage, memory, planning, reasoning, and human-in-the-loop workflows.
- Design end-to-end generative AI platforms with prompt orchestration, RAG pipelines, vector databases, and LLM integrations.
- Define modular, microservices-based, API-first architectures for AI copilots and autonomous systems.
- Evaluate and integrate agentic frameworks including LangChain, LlamaIndex, AutoGen, and CrewAI.
- Establish production-grade observability, monitoring, evaluation, experimentation, guardrails, safety, governance, and cost optimization.
- Lead architecture across LLMOps, MLOps, platform operations, cloud infrastructure, Kubernetes deployments, CI/CD pipelines, and infrastructure as code.
- Ensure scalability, security, resilience, and production readiness of AI workloads.
- Partner with data science, product, and business teams to translate AI use cases into platform capabilities.
- Mentor senior engineers and architects and set engineering standards, reference architectures, and best practices.
- Act as a technical thought leader for enterprise AI platform strategy.
Requirements
- 12–15 years of experience in platform engineering or architecture with strong distributed-systems expertise.
- Deep expertise in AWS, Azure, or GCP and Kubernetes-based architectures.
- Hands-on experience with LLMs, RAG architectures, and vector databases such as Pinecone, FAISS, or Weaviate.
- Strong understanding of agentic frameworks, multi-agent systems, and orchestration patterns.
- Experience with LLMOps and MLOps, including model deployment, monitoring, evaluation, lifecycle management, and version management.
- Proficiency in microservices, APIs, event-driven systems, scalable backend engineering, and system design.
- Strong coding experience in Python, Java, or Go.
- Experience with real-time and batch data platforms and large-scale data processing.
- Understanding of AI safety, governance, and responsible AI frameworks.
- Experience building enterprise AI copilots or autonomous workflows is desirable.
- Exposure to reasoning frameworks, chain-of-thought orchestration, and agent memory systems is desirable.
- Prior consulting or client-facing experience leading AI-driven transformations is desirable.
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