Technozis
Website:
technozis.com
Job details:
LLMOps (LLM Platform Engineering) Lead / AI Platform Architect
Python coding is must.
Role Overview
We are looking for a Lead – LLMOps / AI Platform Architect to drive the design, development, and evolution of enterprise-scale LLM-powered systems and AI platforms.
This role goes beyond traditional MLOps — you will architect next-generation AI capabilities, including RAG systems, agentic workflows, enterprise copilots, and decision intelligence platforms, while ensuring they are scalable, secure, and production-ready.
NOTE: This is a hands-on architecture and platform leadership role, focused on building innovative AI systems — not a pure operations/support function.
Key Responsibilities
AI Architecture & Platform Design
- Architect end-to-end LLM-based systems, including:
- Retrieval-Augmented Generation (RAG)
- Multi-agent / agentic workflows
- LLM fine-tuning and adaptation strategies
- Define system design patterns for:
- scalability
- low-latency inference
- high-throughput workloads
- Lead architectural decisions across:
- model selection (open-source vs API-based)
- retrieval strategies (vector DB, hybrid search)
- orchestration frameworks (LangGraph, LangChain, etc.)
LLM Platform Engineering
- Design and build enterprise-grade LLM platforms enabling:
- rapid experimentation
- standardized deployment
- reusable AI components
- Establish best practices for:
- CI/CD for ML & LLM systems
- model/version lifecycle management
- evaluation and benchmarking frameworks
- Enable scalable deployment using cloud-native and Kubernetes-based architectures
AI Innovation & Use Case Development
- Lead development of:
- enterprise copilots
- decision intelligence systems
- automation agents
- Drive innovation in:
- prompt engineering strategies
- agent orchestration patterns
- LLM evaluation and feedback loops
- Explore and integrate emerging tools, frameworks, and research in generative AI
Leadership & Team Building
- Build and mentor a high-performing team of:
- AI engineers
- ML engineers
- platform engineers
- Provide technical direction and code-level guidance
- Foster a culture of:
- innovation
- ownership
- engineering excellence
Responsible AI, Security & Governance
- Define and implement guardrails for:
- hallucination control
- prompt injection prevention
- PII/data protection
- Ensure compliance with enterprise-grade security standards
- Establish governance frameworks for:
- model evaluation
- explainability
- auditability
Cross-Functional Collaboration
- Partner with:
- product teams
- business stakeholders
- data/platform teams
- Translate business problems into scalable AI solutions
- Support pre-sales and solution design for AI-driven initiatives
Required Qualifications
- 8+ years of experience in AI/ML, with strong exposure to LLMs / Generative AI
- Proven experience designing and deploying production-grade AI systems
- Hands-on experience with:
- RAG pipelines
- vector databases (FAISS, Pinecone, Milvus, etc.)
- agentic frameworks (LangChain, LangGraph, AutoGen, etc.)
- Strong programming skills in Python
- Experience with cloud platforms (AWS / Azure / GCP)
- Deep understanding of:
- MLOps / LLMOps practices
- containerization (Docker, Kubernetes)
- scalable system design
Preferred Qualifications
- Experience with multi-agent systems or AI copilots
- Familiarity with LLM evaluation frameworks (RAGAS, LangSmith, etc.)
- Experience with fine-tuning / LoRA / PEFT
- Exposure to enterprise AI governance and compliance
- Prior experience in leading teams or architecting platforms
What Makes This Role Unique
- Opportunity to architect enterprise-scale AI platforms from the ground up
- Work on cutting-edge areas like:
- agentic AI
- decision intelligence
- enterprise copilots
- High ownership and visibility across the organization
- Strong balance of:
- innovation
- architecture
- engineering excellence
Click on Apply to know more.