AI Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Architect based in India.

This is a foundational technical leadership role responsible for defining and delivering a scalable AI architecture across a multi-product portfolio.

You will establish the target-state architecture and build shared AI services that product engineering teams can consume.

The role combines hands-on architecture, platform engineering, delivery leadership, security, governance, and AI economics.

You will work across LLMs, RAG, agents, evaluation, observability, cloud infrastructure, and AI security.

Your decisions will help reduce duplication, control costs, improve reliability, and accelerate AI adoption across products.

During the initial phase, you will operate as a hands-on architect and delivery leader before building a dedicated AI Platform team.

This is an opportunity to shape the long-term AI strategy and operating model of a growing enterprise B2B SaaS environment.

Accountabilities

• Define and publish the target-state AI architecture across multiple product lines, establishing clear boundaries between central AI services and application-level capabilities.
• Own architectural decisions covering foundation model providers, orchestration frameworks, vector databases, evaluation and observability platforms, guardrails, agent frameworks, and related technologies.
• Establish architecture decision criteria and maintain a structured decision-record process so significant technical choices are documented, defensible, and revisitable.
• Design AI services with tenant isolation, PII protection, regional data residency, security, and compliance requirements built in from the outset.
• Lead the development of a centralized AI platform, including a model gateway, prompt registry, RAG-as-a-service, guardrails and content safety, evaluation and telemetry capabilities, cost attribution, and audit logging.
• Own the phased delivery roadmap covering discovery, architecture decisions, platform development, migration of existing AI capabilities, and ongoing optimization.
• Partner with product engineering leaders to migrate existing AI features onto shared services while maintaining customer commitments and product continuity.
• Establish operational standards for AI services, including observability, SLOs, incident response, reliability practices, and on-call processes.
• Implement per-request AI cost tagging and unit-economics reporting across features, customers, and models, including tenant-level budgets and rate limits.
• Lead a cross-product AI Council responsible for shared standards, new use-case intake, technology choices, and vendor governance.
• Manage AI infrastructure and tooling vendors, leading build-versus-buy assessments and commercial discussions with Product and Finance stakeholders.
• Represent AI architecture, strategy, roadmap, and technical investment decisions in leadership reviews and technical due-diligence discussions.
• Recruit and lead the AI Platform team as the function expands, establishing an effective operating model between central platform engineers and embedded AI teams.
• Mentor engineers across the organization on AI architecture patterns, evaluation methodologies, security practices, and safe production deployment.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or an equivalent technical discipline.
• 10+ years of engineering experience, including at least 5 years in senior architecture roles within enterprise B2B SaaS environments.
• 3+ years of hands-on production experience developing and operating LLM-based systems, including RAG, AI agents, evaluation, prompt engineering, and inference optimization.
• 3+ years of people-management experience, including recruiting, developing, and leading multiple engineering teams in a global environment.
• Demonstrated experience building an AI or ML platform consumed by multiple product teams, with a track record of delivering shared infrastructure rather than isolated AI features.
• Strong delivery leadership and experience shipping complex platforms on schedule, within budget, and with the operational discipline required for production environments.
• Deep cloud-native architecture expertise across Azure and AWS, with practical knowledge of Kubernetes, infrastructure-as-code, and modern data platforms.
• Strong familiarity with the modern LLM ecosystem, including OpenAI, Anthropic, Azure OpenAI, Amazon Bedrock, open-source models, LangChain or LlamaIndex, vector databases, and observability platforms such as LangSmith or Langfuse.
• Strong understanding of AI security and compliance, including prompt injection, tenant isolation, PII handling, SOC 2, GDPR, and third-party AI vendor risk.
• Ability to communicate complex architecture decisions, technical trade-offs, risks, and investment considerations effectively to executive audiences and technical due-diligence teams.
• Fluency in English, both written and spoken.
• Strong strategic thinking, decision-making, communication, stakeholder management, and problem-solving skills.
• Preferred experience in procure-to-pay, ERP integration, accounts payable, procurement, finance, or adjacent enterprise operations software.
• Experience working within an international, private-equity-backed B2B SaaS organization, particularly one undergoing significant growth or preparing for a liquidity event, is an advantage.
• Experience consolidating AI capabilities across products following mergers or acquisitions is desirable.
• Production experience with agent frameworks such as LangGraph, AutoGen, or custom orchestration, as well as fine-tuning and multi-model routing, is a plus.
• Experience leading technology consolidation programs or central platform teams is preferred.
• Prior involvement in technical due diligence as an owner or advisor is an advantage.

Benefits

• Compensation: Competitive compensation aligned with a senior AI architecture and engineering leadership position.
• Work model: Fully remote from India.
• Working hours: 11:00 AM-8:00 PM IST.
• Employment: Full-time.
• Opportunity to define and implement an enterprise-wide AI architecture from the ground up.
• Significant technical ownership across AI platforms, cloud infrastructure, security, governance, and economics.
• Opportunity to build and lead a dedicated AI Platform team as the function scales.
• Exposure to modern LLM technologies, agentic systems, RAG, AI observability, and multi-cloud architecture.
• High-impact collaboration with product engineering, security, finance, and executive leadership.
• Opportunity to shape AI strategy and shared technology capabilities across a growing B2B SaaS portfolio.
• Inclusive environment focused on innovation, transparency, collaboration, professional growth, and meaningful impact.
• Equal-opportunity workplace with consideration for qualified applicants regardless of protected characteristics.
• Accommodation support is available for candidates who require it during the hiring process.