We are seeking a highly experienced AI Solutions Architect to lead the design, architecture, and enterprise adoption of AI-powered workflow automation solutions across the organization.

This is a strategic and hands-on leadership role for someone who understands enterprise business operations, modern AI technologies, systems integration, and scalable software architecture. The ideal candidate will work closely with business leaders, operational teams, IT, data teams, and external partners to identify high-value automation opportunities and architect intelligent AI-driven solutions that improve efficiency, decision-making, and operational scalability. The AI Solutions Architect will define the organization’s approach to AI-enabled workflow automation, including multi-agent orchestration, enterprise integrations, governance, scalable architecture patterns, and operational best practices.

This role requires both deep technical expertise and the ability to translate complex business challenges into practical, enterprise-ready AI solution JOB SPECIFIC DUTIES & RESPONSIBILITIES

Enterprise AI Architecture: Lead the end-to-end architecture, design, and implementation of enterprise AI automation platforms, intelligent workflows, and AI agent ecosystems.

AI Agent Strategy & Orchestration: Design and govern multi-agent architectures where AI agents collaborate across systems, business functions, and data sources to execute complex operational workflows.

Workflow Transformation: Analyze enterprise business processes and define scalable AI-driven automation strategies that reduce manual effort, eliminate inefficiencies, and improve operational performance.

Solution Leadership: Define architectural standards for prompts, agent behaviors, orchestration logic, integrations, human approval flows, escalation paths, observability, and governance controls.

Stakeholder Partnership: Work closely with executive leadership, business stakeholders, operational teams, IT, and data teams to align AI initiatives with business priorities and transformation goals.

Platform & Integration Oversight: Oversee integrations between AI platforms, enterprise applications, APIs, databases, cloud infrastructure, productivity tools, and document management systems.

Technical Leadership: Provide architectural guidance and technical leadership for complex AI implementations, solution reviews, troubleshooting, and enterprise scalability challenges.

Governance, Security & Responsible AI:



Establish best practices for AI governance, security, privacy, access control, auditability, compliance, and responsible AI adoption across the organization.

Full Stack & Engineering Oversight: Guide engineering teams across front-end, back-end, API, cloud, data, and integration layers to ensure delivery of scalable and maintainable AI solutions.

AI Operations & Continuous Improvement: Define monitoring frameworks, evaluation standards, performance metrics, and optimization strategies for deployed AI systems and workflows.

Documentation & Standards: Develop enterprise standards, architectural documentation, implementation frameworks, operational procedures, and reusable design patterns for AI automation initiatives.

REQUIRED EXPERIENCE AND SKILLS

10+ years of experience in software engineering, enterprise architecture, automation, or AI solution delivery roles.

Proven experience designing and deploying enterprise-scale AI, automation, or workflow orchestration solutions.

Robust understanding of large language models (LLMs), AI agents, prompt engineering, orchestration frameworks, and AI-powered business workflows.

Experience architecting integrations across APIs, enterprise systems, cloud platforms, databases, and third-party services.

Deep understanding of enterprise application architecture, system design, scalability, authentication, and secure integration patterns.

Strong experience with workflow automation platforms, AI tooling ecosystems, and orchestration technologies.

Experience leading technical solution design sessions and translating business requirements into scalable technical architectures.

Strong knowledge of software engineering best practices, DevOps principles, CI/CD, observability, and operational support models.

Excellent stakeholder management and communication skills, with the ability to explain complex technical concepts to non-technical audiences.

Demonstrated ability to lead cross-functional initiatives and drive enterprise technology adoption.

Strong analytical thinking, problem-solving, and strategic decision-making capabilities. REQUIRED SKILLS





AI & Automation Platforms: Strong understanding of AI platforms, LLM ecosystems, agent frameworks, workflow orchestration tools, and enterprise automation technologies.

AI Agent Architecture: Experience designing AI agents with structured roles, tools, memory, context handling, guardrails, escalation logic, and human-in-the-loop workflows.

Prompt Engineering & AI Reliability: Ability to design, evaluate, and optimize prompts, reasoning workflows, structured outputs, and AI response quality for enterprise use cases.

Enterprise Integrations: Hands-on expertise with REST APIs, webhooks, middleware, authentication frameworks, enterprise connectors, and system interoperability.

Data & Information Architecture: Strong understanding of databases, structured and unstructured data, document processing, vector search, embeddings, and knowledge retrieval systems.

Cloud & Platform Engineering: Experience with cloud-native architectures, deployment pipelines, infrastructure management, security controls, and scalable distributed systems.

Software Engineering: Strong proficiency in Python, JavaScript, TypeScript, or similar modern development technologies.

Architecture Governance: Experience defining architectural standards, reusable patterns, governance controls, and enterprise technology roadmaps.

Enterprise AI Transformation: Experience implementing AI-driven transformation initiatives across finance, operations, customer service, marketing, IT, or shared services functions.

Multi-Agent Systems: Experience building coordinated AI agent ecosystems capable of executing complex multi-step enterprise workflows.

RAG & Knowledge Systems: Experience with Retrieval Augmented Generation (RAG), enterprise knowledge bases, vector databases, embeddings, and document intelligence solutions.

Data & Analytics Platforms: Exposure to modern data platforms, analytics ecosystems, reporting solutions, and enterprise data governance practices.

AI Governance & Compliance: Understanding of responsible AI frameworks, compliance requirements, auditability, explainability, and enterprise AI risk management.

UI & Internal Tooling: Experience designing internal AI-powered tools, operational dashboards, portals, or workflow interfaces.

Agile Delivery Leadership: Experience working within agile delivery environments and leading iterative enterprise solution implementations.

Working Hours: 1:30 PM – 10:30 PM IST.

📌 AI Solutions Architect / AI Business Architect (India)
🏢 Mitra AI
📍 India