Lead Architect

It's fun to work in a company where people truly BELIEVE in what they are doing! _We're committed to bringing passion and customer focus to the business._ **Role overview:** We’re building a next-gen LLMOps team at Fractal to industrialize GenAI implementation and shape the future of GenAI engineering. This is a hands-on technical leadership role for AI engineers with strong ML and DevOps skills — ideal for those who love building scalable systems from the ground up. You will be designing, deploying, and scaling GenAI and Agentic AI applications with robust lifecycle automation and observability. **Required Qualifications:** * 10 - 14 years of experience in working on ML projects that includes product building mindset, strong hands on skills, technical leadership, leading development teams * Model development, training, deployment at scale, monitoring performance for production use cases * Strong knowledge on Python, Data Engineering, FastAPI, NLP * Knowledge on Langchain, Llamaindex, Langtrace, Langfuse, LLM evaluation, MLFlow, BentoML * Should have worked on proprietary and open-source LLMs * Experience on LLM fine tuning including PEFT/CPT * Experience in creating Agentic AI workflows using frameworks like CrewAI, Langraph, AutoGen, Symantec Kernel * Experience in performance optimization, RAG, guardrails, AI governance, prompt engineering, evaluation, and observability * Experience in GenAI application deployment on cloud and on-premises at scale for production using DevOps practices * Experience in DevOps and MLOps * Good working knowledge on Kubernetes and Terraform * Experience in minimum one cloud: AWS / GCP / Azure to deploy AI services * Team player with excellent communication and presentation skills **Must have skills:** * Product thinking that includes ideation, prototyping, and scale internal accelerators for LLMOps * Architect and build scalable LLMOps platforms for enterprise-grade GenAI systems * Design and manage end-to-end LLM pipelines from data ingestion and embedding to evaluation and inference * Drive LLM-specific infrastructure**:** memory management, token control, prompt chaining, and context optimization * Lead scalable deployment frameworks for LLMs using Kubernetes and GPU-aware scaling * Build agentic AI operations capabilities including agent evaluation, observability, orchestration and reflection loops * Guardrails & Observability: Implement output filtering, context-aware routing, evaluation harnesses, metrics logging, and incident response * Platform Automation for LLMOps: Drive end-to-end automation with Docker, Kubernetes, GitOps, DevOps, Terraform, etc. **Product Thinking**: Ideate, prototype, and scale internal accelerators and reusable components for LLMOps **GenAI Engineering**: Productionize LLM-powered applications with modular, reusable, and secure patterns **Pipeline Architecture**: Create evaluation pipelines — including prompt orchestration, feedback loops, and fine-tuning workflows **Prompt & Model Management**: Design systems for versioning, AI governance, automated testing, and prompt quality scoring **Scalable Deployment**: Architect cloud-native and hybrid deployment strategies for large-scale inference **Guardrails & Observability**: Implement output filtering, context-aware routing, evaluation harnesses, metrics logging, and incident response **DevOps & Platform Automation**: Drive end-to-end automation with Docker, Kubernetes, GitOps, Terraform, etc. **Must-Have Technical Skills** * **LLMOps frameworks**: LangChain, MLflow, BentoML, Ray, Truss, FastAPI * **Prompt evaluation and scoring systems**: OpenAI evals, Ragas, Rebuff, Outlines * **Cloud-native deployment**: Kubernetes, Helm, Terraform, Docker, GitOps * **ML pipeline**: Airflow, Prefect, Feast, Feature Store * **Data stack**: Spark/Flink, Parquet/Delta, Lakehouse patterns * **Cloud**: Azure ML, GCP Vertex AI, AWS Bedrock/SageMaker * **Languages**: Python (must), Bash, YAML, Terraform HCL (preferred) If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us! ### **Hiring Related Queries** India: [[email protected]](mailto:[email protected]) Outside India: [[email protected]](mailto:[email protected]) This inbox does not process resume submissions. All applications must be made through posted job openings Not the right fit?  Let us know you're interested in a future opportunity by clicking _Introduce Yourself_ in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!