Fractal

Lead Architect

Fractal  •  Bengaluru, IN (Hybrid)  •  1 month ago
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Job Description

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.

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: HiringsupportIndia@fractal.ai

Outside India: HiringsupportROW@fractal.ai

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Fractal

About Fractal

Fractal is a globally recognized Enterprise AI company with a vision to power every human decision in the enterprise.

Fractal’s suite of businesses includes Asper.ai (enabling interconnected decisions for revenue growth) and Analytics Vidhya (one of the world’s largest data science communities). Fractal incubated Qure.ai, a global healthcare AI leader enhancing the rapid identification and management of tuberculosis, lung cancer, and stroke. Fractal’s dedicated AI research team is focused on foundational AI advancements, including knowledge-based foundational models, reasoning-based systems, and agentic systems. The team has launched successful products such as MarshallGoldsmith.ai, Vaidya.ai, Kalaido.ai, and the open-source reasoning model Fathom-R1-14B.

Fractal currently has 5500+ employees across 18 global locations including The United States, Canada, UK, Netherlands, Ukraine, India, Singapore, South Africa, UAE, and Australia.

Named Leader by Forrester

Forrester Wave: Customer analytics service Q2 2025

Named Leader by Everest Group

Everest Group Peak Matrix Assessment 2025 for AI and Analytics Services

Great Place to Work

8th year running. Certifications received for India, USA, Australia, and the UK.

‘India’s Best Workplaces for Women’ for five years running by the Great Place to Work® Institute.

For more information, visit fractal.ai

Industry
Consulting & Advisory
Company Size
5,001-10,000 employees
Headquarters
New York
Year Founded
2000
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