Senior AI Architect

Company Description

DataZymes is transforming pharmaceutical analytics by delivering cutting-edge data-driven digital products tailored to address modern challenges in the Pharma Commercial space. By focusing on creating intuitive and empowering user experiences, DataZymes bridges the gap between traditional consulting firms and rigid technology solutions. The company specializes in integrating, managing, and securing data, layered with advanced applications for interactive, machine-driven, human-assisted analysis. Committed to innovation, DataZymes helps its clients navigate a Big Data world with speed, adaptability, and efficiency.

Role Description

This is a full-time, on-site role for a Senior AI Architect based in Bengaluru. The Senior AI Architect will lead AI-driven architectural design and development, develop scalable software solutions, and oversee the seamless integration of AI platforms. The role entails guiding complex projects and collaborating with cross-functional teams to deliver innovative AI solutions to drive data-driven decision-making in the pharmaceutical domain.

SOLUTION ARCHITECTURE

•Own end-to-end solution architecture for complex agentic AI engagements: define agent topology, orchestration patterns, data flows, and integration surfaces.

•Select and justify orchestration approaches (LangGraph, AutoGen, CrewAI, custom) based on use case complexity, latency requirements, and client constraints.

•Design RAG and knowledge retrieval architectures: embedding strategy, index design, hybrid search, knowledge graph schemas for pharma entity networks (drug-HCP-trial-indication).

•Define guardrail frameworks, human-in-the-loop escalation patterns, and graceful failure modes for production agents.

•Create architecture decision records (ADRs) and reusable reference architectures for the firm's agentic AI playbook.

•Evaluate and recommend new frameworks, models, and tooling; maintain a technology radar for agentic AI.

TECHNICAL LEADERSHIP

•Set and enforce code quality, testing, and deployment standards across the team's agent implementations.

•Lead technical design reviews; provide architectural sign-off before new agent systems enter staging.

•Mentor AI Engineers and Sr. AI Engineers on system design, pharma domain context, and production engineering.

•Partner with the Director on long-horizon capability planning and technology investment decisions.

PHARMA DOMAIN APPLICATION

•Translate pharma commercial, medical affairs, and clinical operations requirements into architecturally sound agent designs.

•Ensure compliance architecture: audit trail design, data lineage, 21 CFR Part 11 traceability, and HIPAA-compatible data handling patterns.

•Architect intelligent document processing solutions for regulatory submissions, CSRs, HEOR dossiers, and label intelligence.

WHAT YOU BRING

TECHNICAL DEPTH (REQUIRED)

•7+ years in software or ML engineering; 3+ years architecting production LLM or agentic AI systems.

•Deep expertise in at least two agentic frameworks (LangGraph, AutoGen, CrewAI, custom agent loops); ability to extend and debug framework internals.

•Advanced RAG architecture: multi-index strategies, late interaction models (ColBERT), knowledge graph construction, retrieval evaluation (RAGAS, custom evals).

•Strong API and integration architecture: REST, GraphQL, event streaming, webhook patterns.

•Cloud-native architecture: AWS, Azure, or GCP. IaC (Terraform/CDK), managed AI services, observability stacks.

•Experience with model evaluation, evals-driven development, and LLM cost/quality optimization.

•MCP (Model Context Protocol) implementation experience strongly preferred.

PHARMA / LIFE SCIENCES DOMAIN (REQUIRED)

•Solid understanding of pharma commercial data ecosystems: Rx/claims, NPI analytics, market access, brand performance.

•Hands-on experience designing systems for regulated data environments: GxP, 21 CFR Part 11, HIPAA.

•Exposure to two or more of: medical affairs, RWE, clinical operations, HEOR, regulatory intelligence.

LEADERSHIP & COMMUNICATION (REQUIRED)

•Experience leading technical design processes across multi-functional delivery teams.

•Ability to produce rigorous architectural documentation (ADRs, system diagrams, data flow specs) consumed by both engineers and non-technical stakeholders.

•Comfortable presenting architecture trade-offs to clients and internal leadership.

GOOD TO HAVE

•Experience with Veeva Vault, IQVIA, or Symphony Health platform architecture.

•Knowledge of RLHF, fine-tuning, and model adaptation workflows.

•Familiarity with EU AI Act and FDA AI/ML guidance for regulated environments.

•Prior consulting or services-firm delivery experience.

HOW SUCCESS IS MEASURED

Architecture sign-off on all production agent deployments — no critical design defects post-launch.

•Two or more reference architectures published to the internal playbook within the first year.

•Measurable reduction in re-architecture cycles on team-built systems.

•Positive peer and client feedback on clarity and quality of technical documentation.

•Quarterly technology radar updated with evaluated frameworks and tooling recommendations.