Generative AI Architect

4 weeks ago

Delhi, Delhi, India BECKON DELVE Full time

Job Title : Generative AI Architect

Experience : 5 to 9 years

Location : Remote

Work Hours :

  • Engineer 1 : 7 AM 3 PM EST
  • Engineer 2 : 10 AM 6 PM EST
Joiner Requirement : Immediate Joiner Preferred

Role Overview :

We are looking for a hands-on Generative AI Architect with strong experience in designing, developing, and deploying scalable AI/ML infrastructure, focusing on LLMs, MLOps, cloud-native architectures, and automation-first platforms. The ideal candidate will work closely with cross-functional teams to implement and optimize large-scale AI solutions in a secure and compliant environment.

Key Responsibilities (KRA) :

- Architect, design, and deploy Generative AI and LLM-based solutions in cloud and hybrid environments

- Build and optimize scalable and repeatable MLOps pipelines using modern tools and frameworks

- Collaborate with data scientists, ML engineers, and DevOps teams to productionize AI/ML models

- Ensure infrastructure scalability, observability, and security for AI workloads

- Implement best practices for version control, model governance, and CI/CD for ML pipelines

- Develop automation and self-service capabilities to support rapid experimentation and model deployment

- Advocate and implement Infrastructure-as-Code (IaC) and GitOps workflows using Terraform and Git

- Integrate responsible AI frameworks and enforce policy-as-code for ethical AI deployment

- Drive platform improvements with a focus on developer experience and enablement

- Collaborate on system integration with APIs, cloud-native services, and enterprise-grade data platforms

Primary Skillsets :

- 5+ years of experience in AI/ML infrastructure, MLOps, platform engineering, or cloud architecture

- Proven hands-on experience with Large Language Models (LLMs), Transformers, or Generative AI frameworks

- Deep expertise in building and maintaining Kubernetes-based AI workloads in production

- Strong proficiency in Terraform and Git-based infrastructure workflows (GitOps)

- Experience with popular MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, etc.)

- Proficient in scripting with Python and Bash for automation and orchestration

- Deep understanding of cloud services across AWS / Azure / GCP (compute, storage, networking, security)

- Knowledge of model security, governance, and responsible AI practices

- Familiarity with container security, identity management, and policy-as-code (OPA, Kyverno)

Secondary Skillsets (Preferred) :

- Experience with LLM fine-tuning, RAG (Retrieval-Augmented Generation), vector databases (e.g., FAISS, Pinecone)

- Familiarity with prompt engineering and custom model deployment

- Exposure to Microsoft Power Platform or Dynamics 365 integration

- Experience working with Google Cloud AI/ML services

- Familiarity with observability and logging tools like Prometheus, Grafana, ELK/EFK, and OpenTelemetry
(ref:hirist.tech)

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