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Lead AI Architect-covosant

gravityer.com

Location

Hyderābād, Telangana, India

Salary

Not disclosed

Employment

Contractor

Experience

10-18 years

Job overview

Complete role details

Location

Hyderābād, Telangana, India

Employment type

Contractor

Workplace

Onsite

Experience

10-18 years

Seniority

Lead

Education

Bachelor's degree

Posting date

16 Jul 2026

Closing date

24 Nov 2026

Requisition ID

6a58fda427dc125453152e87

Skills

AzureDockerGCPKubernetesLLMMachine LearningPythonPyTorchscikit-learnTensorFlow

Role details

Job description

Lead AI Architect (10-18 years) – Hyderabad (onsite)

We are seeking a highly experienced Lead AI Architect to anchor technical delivery for enterprise-grade Agentic AI and machine learning projects. You will be responsible for translating complex solution blueprints into production-ready systems, guiding engineering teams, and ensuring scalability and compliance across diverse industries.

Key Responsibilities

  • Own the end-to-end technical architecture and solution integrity for AI/ML project delivery.

  • Translate solution blueprints into detailed technical designs, backlogs, and integration plans.

  • Lead detailed design reviews with a focus on AI platform, MLOps, and Agentic AI best practices.

  • Select and implement appropriate frameworks, APIs, and cloud-native services for production environments.

  • Serve as the technical anchor for customer-facing delivery and guide engineering teams on implementation strategies.

  • Oversee model training, deployment workflows, LLMOps, and observability integrations.

  • Ensure compliance with enterprise and regulatory standards like NIST AI RMF and the EU AI Act.

Required Skills & Experience

  • 10+ years in software architecture or engineering, with 5+ years specifically in applied AI/ML system delivery.

  • Expertise in Python development and major ML frameworks (PyTorch, TensorFlow, Scikit-learn).

  • Deep understanding of LLMs, RAG pipelines, and vector databases (e.g., Pinecone, Qdrant).

  • Proficiency with MLOps/LLMOps tools such as MLflow, Kubeflow, and Argo.

  • Hands-on experience with cloud AI infrastructure on GCP (Vertex AI) or Azure (Azure ML/OpenAI).

  • Strong knowledge of containerization (Docker) and orchestration (Kubernetes).

  • Excellent communication skills with the ability to bridge the gap between technical teams and business stakeholders.