Lead Data Architect

Job Description: Data and AI Lead Architect

We are seeking an experienced Data and AI Lead Architect with 12–15 years of expertise in large-scale data and cloud architecture, particularly on AWS or Google Cloud, who has successfully supported enterprise customers across the US and UK/Europe. The ideal candidate will be based in Kochi (Kerala in general) or Coimbatore (preferred), with flexibility for remote work thereafter. Candidates with 1–2 years of hands-on experience in AI chatbot and LLM development will be given strong preference.

Ideal Candidate Profile

12–15 years of progressive experience as a Data Architect, Cloud Architect, or AI Solution Architect.

Proven expertise in designing enterprise-grade, cloud-native architectures with a mix of data, ML/AI, and customer-facing solutions.

Prior experience driving transformation projects for global customers, particularly in regulated industries across US and Europe.

Capability to combine legacy modernization with cutting-edge AI/Agentic AI design.

Technical Skills

Cloud Infrastructure and Deployment

Deep hands-on expertise with Google Cloud Platform (preferred) or AWS, including services for compute, storage, data warehousing, container orchestration, and serverless deployments.

Strong experience with Vertex AI (on GCP) or equivalent generative AI/ML tooling on AWS (e.g., SageMaker, Bedrock, OpenSearch with vector DB).

Proficiency in MLOps and DevOps pipelines, CI/CD automation, and Infrastructure as Code (Terraform, Deployment Manager, or CloudFormation).

Proven track record architecting highly scalable, resilient, and cost-efficient large-scale data and AI solutions across multiple geographies.

AI/ML and Agentic AI Development

Hands-on exposure to agent-based AI systems, multi-agent frameworks, and autonomous decision-making strategies.

Experience with Generative AI and LLMs (e.g., Gemini, chatGPT, Claude, or enterprise fine-tuned models), including prompt engineering and enterprise data grounding.

Knowledge of frameworks such as LangGraph, LangChain, CrewAI, Sor similar for orchestrating modular, interoperable AI systems.

Experience designing AI Chatbots and enterprise-focused LLM-powered assistants (1–2 years highly preferred).

Strong ability to integrate structured and unstructured data pipelines, vector databases (Pinecone, Supabase), and knowledge graphs into intelligent agent workflows.

Development Tools and Programming

Strong proficiency in Python (primary language), with working experience in Java, Go, JavaScript/TypeScript for backend APIs and integration.

Familiarity with PyTorch, TensorFlow, and scikit-learn for model training, evaluation, and deployment.

Extensive experience with REST/gRPC APIs and cloud-native API development.

Deep understanding of security, IAM policies, compliance, and governance practices in architecting enterprise-grade cloud + AI solutions.

Solution Architecture Expertise

Skilled in modular, scalable AI solution design, following reference architectures from Google Cloud or AWS best practices.

Proven experience in full AI Agent lifecycle management—design, development, deployment, monitoring, retraining—at enterprise scale.

Strong interoperability mindset, enabling agent-to-agent (A2A) and agent-to-application communications in real-world enterprise systems.

Preferred Qualifications

Architect-level certifications in GCP (Professional Cloud Architect / ML Engineer) or AWS (Solutions Architect Professional / ML Specialty).

1–2 years of hands-on experience building AI-driven chatbots and LLM-powered solutions for enterprises.

Prior leadership of global architecture teams serving enterprise customers in the US and Europe.

Strong written and verbal communication skills with experience liaising with CXOs and technical teams internationally.