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Salary
≈ $36k – $83k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Architect · 8+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 27, 2026. First seen by Alion on Sep 21, 2026.

Overview
Company
Impact
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Ecolab propose des solutions et des services en matière d’eau, d’hygiène et de prévention des infections qui contribuent à rendre le monde plus propre, plus sûr et plus sain, protégeant ainsi les personnes et les ressources vitales.

Lead AI Solutions Architect

Job Summary

As the AI Solutions Architect - Legal, you will lead the architecture, design, and delivery of enterprise AI solutions that transform how Legal, Compliance, Procurement, and Regulatory stakeholders operate. You will be responsible for translating complex legal business challenges into scalable, secure, governed, and production ready AI solutions that integrate seamlessly with Contract Lifecycle Management (CLM) platforms, legal workflow tools, enterprise systems, and authoritative systems of record.

This is a hands on architecture role, not a purely advisory position. In addition to owning solution architecture and technical direction, you will actively design, develop, validate, and deploy production ready AI capabilities, reference implementations, integrations, and workflow automation solutions.

You will establish architecture patterns, guide platform and technology decisions, evaluate buy versus build opportunities, and ensure AI is embedded into governed and auditable legal processes. Success in this role requires deep technical expertise, strong solution architecture capabilities, and the ability to influence stakeholders across Legal, IT, Security, Compliance, Procurement, and enterprise technology teams.

Key Responsibilities

Solution Architecture & Technical Leadership

  • Architect end-to-end AI enabled legal solutions spanning intake, contract lifecycle management, compliance workflows, legal operations, document intelligence, and post signature insights.
  • Translate business challenges into scalable technical architectures, including application design, workflow orchestration, integration patterns, data flows, security controls, AI services, and deployment models.
  • Define solution blueprints, reference architectures, reusable design patterns, and technical standards for Legal AI initiatives.
  • Lead architecture reviews and technical decision making across legal technology platforms, enterprise systems, and AI capabilities.
  • Drive technology strategy and roadmap recommendations for legal workflow automation and AI enabled legal operations.

AI Solution Design & Delivery

  • Design and deliver production ready AI agents, copilots, orchestration services, APIs, and automation solutions that solve legal business challenges.
  • Develop AI enabled capabilities supporting contract analysis, clause extraction, obligation tracking, document summarization, compliance validation, legal intake, risk identification, and workflow acceleration.
  • Design and implement agentic and multi agent architectures that integrate intelligence services into governed legal workflows.
  • Establish evaluation frameworks, monitoring patterns, observability standards, and performance metrics to ensure reliable AI solution operation.
  • Lead architecture decisions regarding model selection, orchestration approaches, retrieval strategies, and enterprise AI integration patterns.

Enterprise Integration & Platform Architecture

  • Design secure, scalable integrations between AI capabilities, CLM platforms, workflow tools, enterprise applications, and systems of record.
  • Define integration patterns that maintain proper separation between:
    • AI reasoning and intelligence layers
    • Workflow orchestration platforms
    • Business applications
    • Data services
    • Systems of record
  • Ensure legal systems retain authoritative ownership of records, approvals, contracts, and compliance workflows while AI capabilities augment decision making and productivity.
  • Collaborate with enterprise architecture, platform engineering, and security teams to establish scalable solution patterns.

Buy vs. Build & Vendor Evaluation

  • Lead buy versus build assessments for Legal AI capabilities and workflow solutions.
  • Evaluate vendors, platforms, and emerging technologies against business requirements, integration complexity, risk, security, scalability, and total cost of ownership considerations.
  • Provide technical due diligence, architecture recommendations, implementation estimates, and adoption strategies for legal technology investments.
  • Partner with vendors and implementation teams to ensure solutions align with enterprise architecture standards.

Governance, Security & Responsible AI

  • Establish architecture standards supporting Responsible AI, security, privacy, regulatory compliance, auditability, and enterprise governance requirements.
  • Design controls and guardrails that ensure AI solutions operate safely within regulated legal and compliance processes.
  • Partner with Security, Risk, Compliance, and Legal stakeholders to incorporate governance requirements into solution designs.
  • Ensure solutions meet enterprise standards for data protection, access control, monitoring, resiliency, and operational support.

Technical Leadership & Team Enablement

  • Provide architecture leadership, technical mentorship, and implementation guidance to engineers, data scientists, and solution teams.
  • Lead technical design reviews and establish engineering best practices for AI development and deployment.
  • Drive adoption of reusable components, reference implementations, and enterprise solution standards.
  • Influence cross functional teams through technical expertise, strategic thinking, and collaborative leadership.
  • Serve as the primary technical authority for Legal AI architecture and solution design.

Required Qualifications

  • Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical field.
  • 8+ years of experience architecting and delivering enterprise software, workflow, integration, or AI enabled solutions in production environments.
  • Proven experience serving as a Solution Architect, Lead Engineer, Technical Architect, or comparable technical leadership role.
  • Strong hands on software engineering experience with the ability to personally design, develop, test, and deploy production ready solutions.
  • Extensive experience building AI enabled applications leveraging large language models, agentic architectures, retrieval systems, orchestration frameworks, and enterprise AI services.
  • Demonstrated experience architecting enterprise workflows that span multiple business systems, applications, data sources, and organizational stakeholders.
  • Strong proficiency with Python, API design, integration patterns, cloud native development, and modern software architecture principles.
  • Experience leveraging AI assisted development tools (e.g., Claude Code, GitHub Copilot, Cursor, or similar) to accelerate software delivery and solution development.
  • Proven ability to make architecture tradeoff decisions balancing business value, technical complexity, security, scalability, maintainability, and total cost of ownership.
  • Strong communication and facilitation skills with the ability to engage technical teams, business stakeholders, legal professionals, and executive leadership.

Preferred Qualifications

  • Experience implementing or architecting solutions for Contract Lifecycle Management (CLM), legal operations, compliance, procurement, regulatory affairs, or enterprise workflow automation.
  • Familiarity with platforms such as Agiloft, Eudia, ServiceNow, GEP, Harvey AI or similar legal technology ecosystems.
  • Experience designing AI solutions for:
    • Contract review and analysis
    • Clause and obligation extraction
    • Legal research support
    • Compliance validation
    • Legal intake and matter routing
    • Marketing compliance workflows
    • Procurement contracting
  • Knowledge of enterprise architecture frameworks, integration platforms, API management, and workflow orchestration platforms.
  • Experience implementing Responsible AI, AI governance, model evaluation, and enterprise AI monitoring practices.
  • Familiarity with security, privacy, auditability, and risk management requirements associated with regulated business processes.
  • Experience influencing platform, vendor, and architecture decisions at enterprise scale.
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