data and AI Architect

ClifyX Inc; Los Angeles (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

ClifyX Inc. seeks a seasoned Data Architect to design and govern enterprise data platforms, including data mesh and medallion architectures. You will lead AI/Gen AI initiatives, define MCPs, and guide data contracts, lineage, and security across teams.

Expect hands-on work with Snowflake, Databricks, and multiple cloud environments. You will evaluate emerging technologies, build reusable reference architectures, and drive architecture conversations with senior stakeholders in a regulated BFSI

Qualifications

• 15–20 years of experience in data architecture, data engineering, and analytics platforms.
• Strong consulting experience in large BFSI transformation programs.
• Hands-on expertise with Snowflake and Databricks (Lakehouse architecture).
• Experience with cloud data services in AWS, Azure, GCP.

Responsibilities

• Architect enterprise data platforms for data lake, Lakehouse, and streaming systems.
• Design data integration and data pipeline patterns.
• Evaluate new technologies and run proofs of concepts.
• Set data and AI strategy for data organization.
• Establish data quality, lineage and metadata standards.
• Ensure privacy, security and regulatory compliance.
• Drive adoption of responsible AI frameworks.
• Create reusable patterns, templates and reference architectures.
• Lead modernization of data platforms from on-prem to cloud for BFSI clients.
• Implement AI/Gen AI solutions for data value chain with memory, context management and tool usage.
• Define Model Context Protocols to chain reasoning, retrieval, and action models.

Skills

Data architecture

Data engineering

Analytics platforms

Data mesh

Medallion architecture

Gen AI

LLMs

Prompt engineering

Agent frameworks

RAG pipelines

MCPs

Snowflake

Databricks

Cloud platforms

Security and governance

Tools

LangChain

AutoGen

CrewAI

FAISS

Pinecone

Weaviate

Job description

Architect enterprise data platforms for data lake, Lakehouse, streaming systems.

Design data integration and data pipeline patterns

Should be able to evaluate new technologies and run proof of concepts.

Should be able to set data and AI strategy for data organization.

Established data Quality, lineage and metadata standards

Ensured compliance with privacy, security and regulation

Drivers adoption of responsible AI frameworks

Created architectural guardrails

Drive consensus on standards (eg data contracts, lineage) across different data organizations

Reviews design and elevate architectural thinking across teams

Creates reusable patterns, templates and reference architectures

Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation

Design and implement AI and Gen AI solution for data value chain

Strong experience with LLMs, prompt engineering, and agent frameworks (LangChain, AutoGen, CrewAI).

Deep understanding of MCPs, ReAct, Tree of Thought, and AutoGPT-style reasoning.

Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate).

Experience with A2A orchestration, agent memory strategies, and tool calling.

Strong grasp of enterprise architecture, data governance, and security protocols.

Experience with cloud platforms (Azure, AWS, GCP) and MLOps pipelines.

Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation

Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.

Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.

Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate).

Lead enterprise data platform modernization from on-prem to cloud for banking and insurance clients.

Architect and implement scalable solutions using Snowflake and Databricks on AWS and Azure

Design and implement AI and Gen AI solution for data value chain

Design data integration pipelines (batch, real-time, big data) and analytics platforms

Define and implement data governance, quality, meta data, and lineage frameworks and should be able to leverage GenAI capabilities.

Act as a trusted advisor to senior business and IT stakeholders

Architect Agentic AI ecosystems using LLMs, vector databases, and orchestration frameworks (LangChain, AutoGen, CrewAI).

Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.

Design Agent-to-Agent (A2A) communication protocols for collaborative multi-agent workflows.

Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.

Generic Managerial Skills, If any

15–20 years of experience in data architecture, data engineering, and analytics platforms

Strong consulting experience in large BFSI transformation programs

Hands-on expertise with Snowflake and Databricks (Lakehouse architecture)

Design and implement AI and Gen AI solution for data value chain

Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation

Experience with cloud data services in aws,azure,gcp

Strong background in data integration, reporting, and big data ecosystems

Experience working in regulated environments with data governance and compliance requirements

Excellent stakeholder communication and leadership skills