AI Architect – Bangalore / Mangalore (Hybrid), India

brihatisglobal; India; Hybrid; INR 5,500,000 - 9,000,000; Full time

Job summary

brihatisglobal is seeking an experienced AI Architect to lead the technical direction of a specialised pod within its Global AI Business Unit. The role focuses on translating complex enterprise challenges into production-ready AI solutions, leading technical RFPs, and mentoring engineering teams across AWS, Azure and GCP.

The AI Architect will oversee end-to-end architectures, review critical code, develop PoCs, and ensure enterprise standards while guiding a multidisciplinary team including

Qualifications

• 8–14 years of relevant professional experience.
• Strong fundamentals in clean, typed Python.
• Knowledge of distributed data processing and first-principles software design.
• Hands-on experience with Generative AI, Agentic AI and LLMs.
• Experience building production-ready AI systems.
• Cloud proficiency across AWS, Azure and/or GCP.
• Strong knowledge of LLMOps, tracing and observability.
• Hands-on experience with modern data platforms such as Databricks and Snowflake.
• Knowledge of retrieval systems and data modelling.
• Proven experience writing technical proposals, scoping deliverables and defending technical estimates.

Responsibilities

• Design scalable, end-to-end AI architectures covering data engineering, model selection, deployment pipelines, evaluation and operational governance.
• Lead technical RFP responses, solution outlines, team composition, effort estimations, risk mitigation and success metrics.
• Act as the primary technical authority when engaging with enterprise IT, security and business stakeholders.
• Establish engineering guidelines for clean, typed Python code and enforce standards around evaluation, traceability and auditability.
• Develop reusable accelerators, reference architectures and evaluation frameworks to improve project delivery.
• Hire, coach and mentor Lead Engineers and AI Engineers while building self-sufficient delivery teams.

Skills

Clean typed Python

Generative AI

LLMs

Distributed data processing

Data platforms Databricks

Snowflake

AWS

Azure

GCP

LLMOps

Observability

Technical proposals

Prototype development

Tools

Databricks

Snowflake

AWS

Azure

GCP

Job description

Location: Bangalore / Mangalore, India (Hybrid)
Experience: 8–14 Years
Employment Type: Full-time
Job Category: Information Technology (IT) & Software; Science & Research

Job Overview

An organisation is hiring an experienced AI Architect to lead the technical direction of a specialised pod within its Global AI Business Unit.

The role involves translating complex enterprise challenges into production-ready AI solutions, leading technical RFP proposals and mentoring engineering teams. The selected professional will be responsible for designing end-to-end architectures, reviewing critical code, developing proof-of-concept prototypes and ensuring enterprise standards across AWS, Azure and GCP.

The AI Architect will lead a multidisciplinary team comprising a Lead Engineer, Senior AI Engineers, AI Engineers and Trainees, reporting to the Principal AI Specialist and AI Business Unit Head.

The organisation is hiring for two distinct pod focus areas:

Option 1: Data & Decisions Pod

• Data Platforms: Lakehouse and Data Warehouse architectures using Databricks, Snowflake or similar platforms, including enterprise migration strategies.
• Semantic & Governance: Advanced data modelling, semantic layers and governance aligned with business metrics.
• Intelligent Applications: Forecasting, supply chain planning and decision-support agents built on modern data platforms.

Option 2: Agentic Systems Pod

• Agentic Architectures: Production-grade agent platforms across AWS, Azure and GCP using cloud-agnostic design principles.
• Governance & Control: Tool integration, permission frameworks, human-in-the-loop approval gates, tracing and evaluation harnesses.
• LLMOps & Enterprise Integration: IT and Operations agents, observability, monitoring and integration with enterprise systems.

Key Responsibilities

• Solution Architecture: Design scalable, end-to-end AI architectures covering data engineering, model selection, deployment pipelines, evaluation and operational governance.
• Pre-Sales & Proposals: Lead technical RFP responses, solution outlines, team composition, effort estimations, risk mitigation and success metrics.
• Technical Leadership: Act as the primary technical authority when engaging with enterprise IT, security and business stakeholders.
• Engineering Excellence: Establish engineering guidelines for clean, typed Python code and enforce standards around evaluation, traceability and auditability.
• Asset Building: Develop reusable accelerators, reference architectures and evaluation frameworks to improve project delivery.
• Team Development: Hire, coach and mentor Lead Engineers and AI Engineers while building self-sufficient delivery teams.

Requirements & Qualifications

Primary Skills – Must Have

• 8–14 years of relevant professional experience.
• Strong fundamentals in clean, typed Python.
• Knowledge of distributed data processing and first-principles software design.
• Hands-on experience with Generative AI, Agentic AI and LLMs.
• Experience building production-ready AI systems.
• Cloud proficiency across AWS, Azure and/or GCP.
• Strong knowledge of LLMOps, tracing and observability.
• Hands-on experience with modern data platforms such as Databricks and Snowflake.
• Knowledge of retrieval systems and data modelling.
• Proven experience writing technical proposals, scoping deliverables and defending technical estimates.

Preferred Qualifications

• Experience in Pharma or Life Sciences, particularly regulated GxP environments.
• Previous experience establishing an AI team, pod or practice from scratch.

Key Performance Traits

• First-Principles Mindset: Deep understanding of retrieval, latency trade-offs and cost optimisation beneath AI frameworks.
• Delivery-Focused: Proven ability to deliver real-world systems used by enterprise clients.
• Adaptable: Comfortable working across different cloud platforms, technology stacks and business domains.
• Clear Communicator: Ability to explain technical concepts to engineering teams and non-technical executive stakeholders.

Salary, Benefits & Career Growth

Salary and benefits have not been disclosed by the employer. Candidates should confirm the compensation package and employment benefits during the selection process.