P

PairSoft

Automates procurement, AP, and document management

AI Architect

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listed

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Engineering, or equivalent is required.
  • At least 10 years of engineering experience, including at least 5 years in senior architecture roles at enterprise B2B SaaS companies.
  • At least 3 years of hands-on production experience with large language model systems, including retrieval-augmented generation, agents, evaluation, prompt engineering, and inference optimization.
  • At least 3 years of people-management experience, including recruiting, motivating, and developing three or more teams in a global setting.
  • A demonstrated track record of building an AI or machine-learning platform consumed by multiple product teams, including designing and shipping shared infrastructure rather than only individual features.
  • Demonstrated delivery leadership, with a record of shipping platforms on time and on budget with production operational discipline.
  • Deep cloud-native architecture experience on Azure and AWS, with familiarity with Kubernetes, infrastructure as code, and modern data platforms.
  • Fluency across the modern large language model ecosystem, including OpenAI, Anthropic, Azure OpenAI, Amazon Bedrock, open-source models, LangChain or LlamaIndex, vector databases, and observability tools such as LangSmith or Langfuse.
  • A clear understanding of AI security and compliance, including prompt injection, tenant isolation, personally identifiable information handling, SOC 2, GDPR, and vendor-risk considerations for private-equity-owned SaaS companies.
  • Ability to communicate architecture decisions and tradeoffs to executive audiences, including private-equity sponsors and technical due-diligence teams.
  • Fluency in English.

Responsibilities

  • Define and publish the target-state AI architecture across product lines, including boundaries between central services and application layers.
  • Own technology decisions for foundation-model providers, orchestration frameworks, vector stores, evaluation and observability platforms, guardrails, and agent frameworks.
  • Establish architecture decision criteria and a decision-record process so significant decisions are defensible, documented, and revisitable.
  • Design tenant isolation, personally identifiable information handling, and regional data residency from the outset, working with the Chief Information Security Officer on the security envelope.
  • Lead development of the central AI platform, including a model gateway, prompt registry, retrieval-augmented-generation-as-a-service, guardrails and content safety, evaluations and telemetry, cost attribution, and audit logging.
  • Own the phased roadmap covering discovery and decisions, platform development, migration of existing product AI features to the platform, and optimization.
  • Partner with product engineering leaders across product lines to migrate existing AI features onto the central platform without disrupting customer commitments.
  • Set operational standards for observability, service-level objectives, incident response, and the on-call model for AI services.
  • Establish per-request cost tagging and an AI unit-economics dashboard, track cost per feature, customer, and model, and enforce per-tenant budgets and rate limits.
  • Chair a cross-product AI Council to govern shared standards, new use-case intake, and vendor decisions.
  • Own vendor relationships for AI infrastructure and tooling, and lead build-versus-buy analysis and commercial negotiations with product and finance partners.
  • Prepare and represent AI architecture and the roadmap in leadership reviews and private-equity sponsor conversations, including technical due diligence.
  • Recruit and lead the AI Platform team as the function grows.
  • Establish the operating model between the central platform team and embedded AI engineers across product lines.
  • Mentor engineers across the portfolio on AI patterns, evaluation practices, and safe deployment.

Desired Qualifications

  • Domain experience in procure-to-pay, ERP integration, accounts payable, procurement, or adjacent finance and operations software.
  • Prior experience at an international private-equity-backed B2B SaaS company, ideally one that went through or is preparing for a liquidity event.
  • Experience integrating and consolidating AI capabilities across products acquired through mergers and acquisitions.
  • Direct production experience with agent frameworks such as LangGraph, AutoGen, or custom orchestration, fine-tuning, and multi-model routing.
  • Experience leading a central platform team through a technology consolidation program.
  • Prior participation in technical due diligence as an owner or advisor.

About the Company

PairSoft

Automates procurement, AP, and document management

PairSoft provides automated procurement and document management solutions for medium to large organizations across industries like healthcare, higher education, hospitality, manufacturing, distribution, non-profit, and professional services. It offers procurement automation, accounts payable (AP) automation, and document management that work together to streamline purchasing processes. The platform supports end-to-end workflow—from catalog and supplier management to approvals and invoice processing—typically delivered on a subscription basis with pricing tailored to a client’s size and needs, plus implementation support and training. Its software aims to move organizations from paper-based processes to a paperless system, offering complete visibility and analytics to help users make better purchasing decisions, save time, and reduce costs while boosting productivity and collaboration among teams.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Miami, FL
Founded
1997

Recently Posted Jobs

Explore more opportunities at PairSoft

See more jobs