Technozis
Website:
technozis.com
Job details:
LLMOps Lead / AI Platform Architect
Location: Bangalore, India
Experience: 9–15 Years
Open Positions: 4
Compensation: Up to ₹60 LPA
Employment Type: Full-Time
Role Overview
We are looking for experienced LLMOps / AI Platform Architects to drive the design, development, and evolution of enterprise-scale LLM-powered systems and AI platforms.
This is a hands-on architecture and platform engineering role, focused on building innovative, scalable, secure, and production-ready AI systems.
The role involves architecting next-generation AI capabilities including RAG systems, Agentic AI workflows, enterprise copilots, and decision intelligence platforms.
*Note: This is not a pure LLM operations or support role. Strong hands-on engineering and architecture experience is required.
Key Responsibilities
AI Architecture & Platform Design
- Architect end-to-end LLM-based systems including RAG pipelines, multi-agent workflows, LLM adaptation, and enterprise AI solutions.
- Define architecture patterns for scalability, low-latency inference, and high-throughput workloads.
- Lead technical decisions around model selection, retrieval strategies, vector databases, hybrid search, and AI orchestration frameworks.
- Design scalable and reusable AI platform components.
LLM Platform Engineering
- Design and build enterprise-grade LLM platforms supporting rapid experimentation and standardized deployment.
- Establish best practices for CI/CD across ML and LLM systems.
- Define model and version lifecycle management practices.
- Build evaluation and benchmarking frameworks for LLM applications.
- Enable scalable deployment using cloud-native and Kubernetes-based architectures.
GenAI & AI Innovation
- Lead development of enterprise copilots, automation agents, and decision intelligence solutions.
- Develop advanced prompt engineering and agent orchestration strategies.
- Design LLM evaluation and feedback mechanisms.
- Research and integrate emerging Generative AI tools, frameworks, and technologies.
Leadership & Team Building
- Build and mentor teams of AI Engineers, ML Engineers, and Platform Engineers.
- Provide technical direction and code-level guidance.
- Promote engineering excellence, innovation, and ownership.
Responsible AI, Security & Governance
- Design guardrails for hallucination control and prompt injection prevention.
- Implement PII and data protection mechanisms.
- Establish frameworks for model evaluation, explainability, auditability, and enterprise AI governance.
Cross-Functional Collaboration
- Partner with product, business, data, and platform teams.
- Translate business requirements into scalable AI solutions.
- Support solution design and pre-sales activities for AI initiatives
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Mandatory Skills & Qualifications
- 9–15 years of overall AI/ML experience.
- Strong hands-on experience with LLMs and Generative AI.
- Proven experience designing and deploying production-grade AI systems.
- Strong hands-on experience with: RAG pipelines; Agentic AI / multi-agent systems; Vector databases such as FAISS, Pinecone, or Milvus; LangChain / LangGraph / AutoGen or similar frameworks
- Strong Python programming and coding skills — mandatory.
- Experience with AWS, Azure, or GCP.
- Strong understanding of LLMOps / MLOps practices.
- Experience with Docker and Kubernetes.
- Strong understanding of scalable AI system architecture and platform engineering.
- Strong understanding of prompt engineering and LLM observability.
Preferred Qualifications
- Experience building multi-agent systems or enterprise AI copilots.
- Experience with LLM evaluation frameworks such as RAGAS or LangSmith.
- Experience with LLM fine-tuning, LoRA, or PEFT.
- Exposure to enterprise AI governance and compliance.
- Experience leading AI/ML engineering teams or architecting enterprise AI platforms.
What Makes This Role Unique
- Opportunity to architect enterprise-scale AI platforms.
- Work on cutting-edge areas including Agentic AI, enterprise copilots, RAG, and decision intelligence.
- High ownership and visibility across AI initiatives.
- Strong combination of architecture, innovation, and hands-on engineering.
Please apply only if you have strong hands-on LLM/GenAI engineering and architecture experience.
Click on Apply to know more.