Chief AI Architect at Innovapptive

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

17 Feb, 26

Salary

0.0

Posted On

19 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Architecture, AI Governance, Multi-Agent Systems, SaaS, Data Pipelines, Vector Databases, AI Security, Compliance Frameworks, Communication Skills, System Design, AI Engineering, Model Selection, Agent Orchestration, Telemetry, Cost Management, Prompt Design

Industry

Mobile Computing Software Products

Description

Chief AI Architect (Enterprise AI Systems & Governance) Location: Hyderabad, India Employment Type: Full-Time; Salaried Compensation: Base Salary, Bonus, Stock Options, Medical Job Description About Us Innovapptive is a category-defining SaaS company building the world’s most advanced AI-powered Connected Worker Platform for the industrial sector. Headquartered in Houston, TX, and backed by Vista Equity Partners, Innovapptive is on a mission to reimagine how industrial work gets done — connecting frontline workers, back-office systems, and assets in real time to drive higher safety, reliability, and productivity. Our platform is trusted by some of the world’s largest enterprises — including Shell, Hess, Cenovus Energy, W.R.Grace, Westlake Chemicals, UNICEF, Kimberly Clark, Scott Miracle Gro, and Newmont Mining to name a few, and across chemicals, energy, mining, and manufacturing industries. These customers have achieved tangible, hard-dollar results, such as: Over $40 million in annual EBITDA savings at a single enterprise. 10× frontline productivity improvements through mobile-first and AI-enabled workflows. 15–20% maintenance cost reductions and significant uptime gains across plants and sites. Innovapptive is recognized by leading industry analysts for its differentiated value creation model: Named a Leader in the Frost & Sullivan Industrial Connected Worker Radar. Featured by Gartner in “Connected Factory Worker” research and the Hype Cycle for Manufacturing Operations Strategy. Cited by LNS Research for delivering 3–5× greater value than point solutions through unified OT–IT execution, AI/vision innovation, and field-proven ROI. Our growth is backed by Tiger Global Management and Vista Equity Partners, one of the world’s premier software investors, known for scaling high-performance SaaS companies. Together, we are building the next-generation AI Powered Connected Worker Platform, combining cutting-edge technologies — SLM’s, Generative AI, Computer Vision, and Intelligent Orchestration — into a unified system that transforms plant operations globally. Today, with over 300+ employees across the U.S., India, and ANZ, Innovapptive stands at a pivotal inflection point: with an ambition to scale to $100M ARR within the next 3-4 years by industrializing every aspect of our product, engineering, and customer delivery systems. The Role The Chief AI Architect is the strategic and technical authority responsible for the Enterprise AI Reference Architecture at Innovapptive. Reporting directly to the SVP of Engineering & Technology, this role establishes how AI Agents, Models, Data, and Control Systems interact—ensuring reliability, security, and cost efficiency as AI becomes a core layer of the Connected Worker Platform. This leader combines deep systems architecture expertise with pragmatic engineering instincts, designing for scale while guiding lean execution. They partner closely with the AI Platform Architect, VP of Technology & Architecture, and Engineering Ops** to create a cohesive AI governance and delivery ecosystem. How You Will Make An Impact 1. Define the Enterprise AI Reference Architecture Architect the AI Systems Blueprint—covering model selection, agent orchestration (MCP), data flows, vector stores, governance, and observability. Standardize communication and context-sharing between Agents, microservices, and data systems. Ensure modularity and extensibility for new AI Agent types (Planner, Detect, Assist, Optimize). 2. Establish AI Governance and Trust Framework Build a comprehensive AI Governance Model—covering data ethics, security, prompt versioning, model selection, and human-in-the-loop controls. Define metrics for accuracy, explainability, safety, and drift, with dashboards visible to engineering and leadership. Implement AI observability standards across telemetry (Sentry, Datadog) and cost management frameworks. 3. Integrate AI Architecture with Core Platform Partner with the AI Platform Architect to embed governance and monitoring within the MCP control plane. Define APIs and integration patterns for connecting LLMs, vector databases, and industrial data sources (OSI PI, SAP, Maximo). Guide teams on designing AI features that extend existing modules rather than duplicating them. 4. Build AI Engineering Standards and Culture Author of the AI Engineering Playbook—principles for AI system design, testing, and documentation. Define best practices for prompt design, validation, and cost optimization (“AI SRE” principles). Conduct architecture reviews and mentoring sessions to upskill engineers on AI systems thinking. 5. Partner for Business Value and Adoption Translate executive KPIs (velocity, reliability, cost take-out) into AI architecture objectives. Work with Product and Customer Success to measure and communicate value created by AI-powered features. Collaborate with Security, Finance, and Legal to maintain auditability and compliance. What You Bring to The Team 15 + years in software architecture, including 5 + years in AI platform or systems architecture. Proven experience building AI governance or multi-agent systems for SaaS or enterprise products. Strong understanding of LLMs, retrieval architectures, and agent frameworks (LangChain, CrewAI, Semantic Kernel, DSPy). Deep knowledge of data pipelines, vector databases (Pinecone, Weaviate, Qdrant), and embedding models. Familiarity with AI security and compliance frameworks (ISO 27001, SOC 2, GDPR). Excellent communication and system design skills; able to align executives, architects, and engineers around a shared vision. Success Metrics (FIRST 90-180 Days) AI Reference Architecture Blueprint completed and adopted across engineering teams. Governance Framework operational, including prompt versioning and observability dashboards. MCP governance and telemetry integrated with Platform and DevOps systems. AI Engineering Playbook published and used by engineering and product teams. AI cost and latency metrics visible and controlled across production agents. Why does this Role Matter? AI is now the core operating system of Innovapptive’s future — and architecture is its language of truth. The Chief AI Architect ensures that our AI capabilities are not just powerful, but responsible, reliable, and governed by design. This leader turns AI innovation into a scalable, trusted platform advantage — building the bridge between experimentation and industrialization. What We Offer Competitive compensation and equity tied to strategic AI delivery milestones. The opportunity to define the AI blueprint for a Vista-backed industrial SaaS scale-up. Flexible engagement model — full-time or fractional leadership. Hybrid work arrangement with periodic travel to Houston HQ for executive alignment. Innovapptive does not accept and will not review unsolicited resumes from search firms. Innovapptive is an equal opportunity employer and is committed to a diverse and inclusive workplace. Qualified applicants will receive consideration for employment without regard to race, color, religion or creed, alienage or citizenship status, political affiliation, marital or partnership status, age, national origin, ancestry, physical or mental disability, medical condition, veteran status, gender, gender identity, pregnancy, childbirth (or related medical conditions), sex, sexual orientation, sexual and other reproductive health decisions, genetic disorder, genetic predisposition, carrier status, military status, familial status, or domestic violence victim status and any other basis protected under federal, state, or local laws.

Responsibilities

The Chief AI Architect is responsible for defining the Enterprise AI Reference Architecture and establishing AI governance and trust frameworks. This role involves integrating AI architecture with the core platform and building AI engineering standards and culture.