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Lead Architect

salary Not Disclosed
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job companyFractal Analytics Private Limited
job location Malur, Bangalore
job experience10 - 6+ years Experience in Hardware / Network Engineer
1 Opening
full_time Full Time

Job Highlights

qualification
All Education levels
gender
All genders
jobShift
5 days working | Day Shift

Job Description

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: HiringsupportIndia@fractal.ai Outside India: HiringsupportROW@fractal.ai 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! Experience Level Senior Level

Other Details

  • It is a Full Time Hardware / Network Engineer job for candidates with 6+ years of experience.

More about this Lead Architect job

  1. What qualifications and experience are required for this Lead Architect position?
    Ans : Candidates should have All Education levels with 10-7 years of experience.
  2. What is the salary and job type for this role?
    Ans : Salary details will be shared during the hiring process.
  3. What shift and timings does this job follow?
    Ans : This Lead Architect job follows a Day shift.
  4. Do you need to visit the office for this job?
    Ans : Yes, candidates need to visit the office and work from the location in Malur, Bangalore.
  5. How many openings are available for this position?
    Ans : There is 1 opening available for this position.
  6. Is this job open for all genders?
    Ans : Yes, this Lead Architect job is open for both male and female candidates.
  7. Where is this job located?
    Ans : This Lead Architect job is located in Malur, Bangalore.
  8. Why should you apply for this Lead Architect job?
    Ans : The employer has not disclosed the salary for this role, but it is a Full Time opportunity with 1 opening available.
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Contact Person

FRACTAL ANALYTICS PRIVATE LIMITED
Posted 10 days ago
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