AI ML Architect in India, India

AI Architect (1272)
Full Time
AI & Data
Axtria is a leading global provider of cloud software and data analytics to the Life Sciences industry. We help Life Sciences companies transform the product commercialization journey to drive sales growth and improve healthcare outcomes for patients. Since our founding in 2010, innovation has been our winning differentiation, and we continue to leapfrog competition with platforms that deploy Artificial Intelligence and Machine Learning. Our cloud-based platforms - Axtria DataMax™, Axtria InsightsIQ™, Axtria SalesIQ™, and Axtria MarketingIQ™ - enable clients to efficiently manage data, leverage data science to deliver insights for sales and marketing planning, and manage end-to-end commercial operations. We work with over 100 Life Sciences companies, many with multiple engagements globally across 75+ countries. We continue to win industry recognition for growth and are featured in some of the most aspirational lists – INC 5000, Deloitte FAST 500TM, NJBiz FAST 50, SmartCEO Future 50, Red Herring 100, and several other growth and technology awards.
Axtria is looking for exceptional talent to join our rapidly growing global team. Axtria is recognized for its organizational culture in both US and India, including certification by the Great Place to Work® Institute. Axtria Institute, our in-house university, offers the best training in the industry and an opportunity to learn in a structured environment. A customized career progression plan ensures every Axtrian is setup for success and able to do meaningful work in a fun environment. We are looking for a AI Architect — a rare blend of AI engineering depth and pharma commercial domain expertise. In this role you will design, build, and govern a fleet of autonomous agents built on Anthropic's Claude Code SDK. These agents will be the backbone of next-generation Commercial Data Platform, automating complex workflows across data ingestion, transformation, insight generation, CRM integration, and commercial analytics for pharmaceutical clients.
Agent Architecture & Design
Define the agent topology for the commercial data platform: data ingestion agents, transformation agents, validation agents, insight narration agents, and CRM-sync agents.
Design agent workflows for pharma commercial use cases including sales force automation, territory management, incentive compensation calculation, marketing attribution, and patient journey analytics.
Build and maintain MCP (Model Context Protocol) servers and custom tool integrations for pharma data sources (IQVIA, Symphony Health, CRM systems, data lakes).
Establish prompt engineering standards, system prompt libraries, and agent persona guidelines for commercial pharma contexts.
Build agentic pipelines that orchestrate Claude Code agents to perform autonomous ETL, data quality checks, anomaly detection, and report generation on pharma commercial datasets.
Develop reusable Claude Code plugins and skill packs tailored to pharma commercial workflows.
Implement agent evaluation frameworks: define metrics, run evals, and continuously improve agent performance and reliability.
Integrate Claude-powered agents with cloud platforms (AWS, Azure, GCP) and pharma data warehouses (Snowflake, Databricks, Redshift).
Commercial Data Platform Development
Drive the architecture of AI-native commercial data platform, ensuring it is modular, scalable, and agent-ready.
Collaborate with product and data teams to translate pharma commercial business requirements into agentic workflows.
Ensure data governance, compliance (HIPAA, GDPR), and security standards are embedded into all agent-driven data pipelines.
Build real-time and batch agent workflows for processing specialty pharmacy data, prescription data, sales performance metrics, and HCP/HCO engagement data.
Design agent-assisted self-service analytics capabilities for commercial operations teams at pharma clients.
Define and enforce Claude Code development best practices, coding standards, and review processes for the engineering team.
Mentor junior and mid-level engineers on agentic AI patterns, prompt engineering, and pharma commercial data concepts.
Lead architectural reviews, design documentation, and technical roadmap planning for the AI agent platform.
Participate in client-facing discussions to explain agent-based platform capabilities to pharma commercial stakeholders.
Collaborate with client success teams to tailor agent deployments to specific commercial model configurations (specialty, rare disease, primary care, oncology).
Deep, demonstrable expertise with Claude Code CLI — including slash commands, hooks, settings configuration, and IDE integrations.
Hands-on experience building agents using the Anthropic Claude Agent SDK and Anthropic API (tool use, multi-turn, computer use).
Strong understanding of Model Context Protocol (MCP) — both consuming MCP servers and building custom MCP server integrations.
Experience with Claude model selection strategy (Opus, Sonnet, Haiku) for different agentic task profiles.
Proficiency in prompt engineering: system prompts, few-shot examples, chain-of-thought, XML-structured outputs, and agent personas.
Familiarity with Claude Code plugin architecture, skill creation, and agentic workflow orchestration.
Software Engineering

• 8+ years of software engineering experience with strong proficiency in Python and/or TypeScript/JavaScript.
• Experience building production-grade agentic or LLM-powered applications with robust error handling, retries, and observability.
• Proficiency with cloud platforms: AWS (Lambda, S3, Glue, SageMaker), Azure, or GCP.
• Strong background in data engineering: ETL/ELT pipelines, data modeling, SQL, and data warehouse technologies (Snowflake, Databricks preferred).
• Experience with REST APIs, GraphQL, and enterprise system integrations (CRM, ERP, data marketplaces).
• Familiarity with containerization and orchestration (Docker, Kubernetes) for deploying agent workloads.

ETL / Data Pipeline Engineering

SQL & Data Modeling

Python / TypeScript

Snowflake / Databricks

HIPAA / Data Governance

LLM Observability & Monitoring

4+ years of experience working in or with pharmaceutical commercial operations, life sciences data, or healthcare analytics.

• Familiarity with pharma commercial data types: prescription data (TRx/NRx), specialty pharmacy data, HCP/HCO master data, sales force sizing, territory alignment, and incentive compensation.
• Understanding of pharma commercial processes: launch readiness, market access, brand planning, CRM (Veeva CRM / Salesforce Health Cloud), and field force effectiveness.
• Knowledge of compliance considerations in pharma data: HIPAA, Sunshine Act, sampling compliance, and data de-identification.
• Exposure to specialty therapy areas (oncology, immunology, rare disease, CNS) and their unique commercial data characteristics.
• Experience building analytics products for commercial pharma clients: dashboards, KPI engines, field reporting, and call plan optimization.

Builder Mindset: Comfortable working in ambiguity, defining standards from scratch, and iterating rapidly toward production quality.
Communication: Can articulate complex agentic AI concepts clearly to both technical and non-technical pharma stakeholders.
Takes end-to-end accountability for agent platform quality, reliability, and business impact.
Works effectively across data science, product, client success, and engineering teams in a globally distributed organization.
Actively follows Anthropic release notes, agentic AI research, and pharma commercial industry trends.

Salary range or hourly pay range for the position

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