Senior Principal

Senior Principal - AI Adoption (Solution Architect)

Location: Bengaluru, India

Experience: 10 to 15+ years

Role Summary:

leading the charge in transforming enterprise SaaS for infrastructure, and AI is at the

core of this revolution. With Lumina, our AI copilot, we are redefining how infrastructure

owners interact with Masterworks, driving smarter, faster, and more efficient decision-making.

We have set up AI Labs to build AI-powered software and transform into an AI-first

company. We have AI initiatives across the products and platforms. We are seeking an

experienced AI Adoption and Solution Architect to design and implement our AI/ML, Gen AI and

agentic AI initiatives, with a focus on building pipelines, evaluation, and LLMOps. This role

involves understanding existing products of and design AI adoption strategies and

architecting the solutions.

Key Responsibilities:

This position offers an opportunity to shape the AI transformation of our organization, working

with cutting-edge technologies and solving complex challenges in a collaborative environment.

• Architectural Blueprinting: Create thorough architectural blueprints and best practices for

designing and implementing autonomous AI systems.

• System Validation and Resilience: In order to ensure compliance with ethical, performance,

and compliance standards for reliable production systems, design and supervise the thorough

architectural evaluation and testing of AI agents, including stress testing, adversarial scenario

simulations, and bias mitigation techniques.

• Stakeholder Advocacy & Collaboration: Work together with the product and solution teams to

match strategic goals with AI architectural projects. Encourage best practices in architecture

and AI-driven innovation throughout the company.

• To guarantee safety, dependability, and compliance, put in place guardrails, human-in-the-

loop procedures, and validation.

• Complex System Integration: Manage the intricate integration of AI agents with databases,

web services, APIs, and other enterprise systems.

• Team Lead: Demonstrated ability to oversee complex AI projects, mentor senior technical

staff, and lead the architectural direction of AI/ML teams.

• Construct and enhance essential architectural elements such as: Tool/Function Integration

Layer, Agent Orchestration Layer, Data Storage and Retrieval Layer and reasoning layer.

Qualifications and Required Technical expertise:

• 10+ years of progressive experience in AI/ML, with a strong track record as solution

architect.

• 5+ years of experience with cloud data platforms for AI architecture, particularly AWS

data services

• 3+ years of experience architecting MPP database solutions (Redshift, Snowflake, etc.)
• Experience in designing and implementing Gen AI solutions including

autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems,

or LLM-driven decision engines).

• Cloud-Native and Hybrid System Architecture, Microservices, RESTful APIs,

Containerization (Docker, Kubernetes)

Extensive hands-on experience with autonomous AI tools and frameworks: LangChain,

Autogen, CrewAI, or architecting custom agentic frameworks.

• Working knowledge of data integration patterns and technologies (ETL/ELT, CDC)
• Proven experience with LLMOps/MLOps pipelines (e.g., Kubeflow, MLflow) and designing

scalable deployment strategies for AI agents in production environments.

• Strong expertise with LLMs (e.g., GPT, Claude, Mistral)
• Experience with one or more programming/scripting languages (Python, SQL, Shell)
• Deep understanding of planning algorithms, decision-making models, and agentic

architectures.

• Understanding of regulatory requirements related to data (Fed Ramp, GDPR, CCPA, etc.)
• Experience with big data technologies (Spark, Hadoop)
• A track record of effectively implementing and refining LLM models for inference in

operational settings.

• Familiarity in implementing LLM models in both on-premises and cloud systems AWS.
• Demonstrated capacity to optimize LLM models for resource usage, memory efficiency,

and inference speed.

• Knowledge of orchestration tools (like Kubernetes) and containerization technologies

(like Docker) for effective and scalable model deployment.

• Bachelor//'s or master//'s degree in computer science or a related field.

Leadership & Soft Skills

• Excellent verbal and written communication skills, with ability to translate complex

technical concepts to varied audiences

• Strong stakeholder management and influencing skills
• Analytical thinking and problem-solving ability
• Project planning and execution capabilities