CHIEF AI & Product OFFICER (CAIPO)

Co-Founder Level | Equity-Based | Remote (India)

Aimyze Software Private Limited | Bengaluru, Karnataka

Remote - Pan India

Series : Pre-Seed

HQ : Bengaluru

Equity Based Role

3-Month Probation

ABOUT AIMYZE

Aimyze Software Pvt. Ltd. is an early-stage AI-powered SaaS startup headquartered in Bengaluru, building intelligent automation and decision-intelligence solutions for the Manufacturing and Enterprise IT sectors. We are developing AI-native platforms that bridge the gap between Operational Technology (OT), Industrial IoT, and Enterprise IT environments - enabling manufacturers and enterprises to unlock actionable intelligence from their operational data.

We are at a pivotal stage of our journey - MVP development is underway, early pilots are being shaped, and the foundational AI architecture is being defined. Our mission is to become the AI backbone for India's industrial and enterprise transformation. We are not building another dashboard - we are building the intelligent operating system for the factory floor and the enterprise.

THE ROLE

This is a founding team role. As Chief AI & Product Officer, you will be the technical and strategic brain behind everything AI at Aimyze. You will own the end-to-end AI architecture, define how we build and deploy intelligent systems across manufacturing, OT/IT, and enterprise environments, and directly lead product development from prototype to production.

We are looking for someone who brings a rare combination: deep hands-on engineering ability, domain expertise in industrial and enterprise environments, and the strategic vision to define where AI can create irreversible competitive advantage for our customers. You will work directly with the Founder & CEO and be a key voice in shaping both product and company direction.

This is not a management-only role. You will code, architect, experiment, and ship. You will also lead a growing team of interns and engineers and eventually build your own AI function.

KEY RESPONSIBILITIES:

AI Architecture & AgenticAI:

- Own the end-to-end AI/ML system architecture - from raw data ingestion to model deployment

- Design and implement Agentic AI workflows - multi-agent orchestration, tool-use agents, and autonomous decision pipelines

- Build and evolve the RAG (Retrieval Augmented Generation) architecture - embedding strategy, chunking, retrieval optimization, and hybrid search

- Set up and manage vector databases (Pinecone / Weaviate / pgvector or equivalent) for semantic search and memory

- Develop time-series processing pipelines for sensor, telemetry, and operational data from manufacturing environments

- Integrate LLMs (OpenAI, Anthropic, open-source models) into production-grade pipelines with reliability and cost efficiency

Manufacturing, OT/IT & Enterprise Integration:

- Lead AI integration with manufacturing systems - MES, SCADA, CMMS, ERP, PLCs, and Edge devices

- Architect data flows from OT (shop floor, sensors, PLCs) to IT (cloud, APIs, analytics) with AI enrichment layers

- Build AI capabilities for industrial use cases - predictive maintenance, anomaly detection, process optimization, quality intelligence

- Understand and integrate with enterprise systems - ERP (SAP/Oracle), HRMS, banking/BFSI platforms - positioning Aimyze for expansion beyond manufacturing

- Define integration patterns for enterprise IT environments - APIs, middleware, event-driven architectures

Product & MVP Development:

- Take end-to-end ownership of MVP & Product development - from concept to deployed, production-grade product

- Work with the CE0&CTO to prioritize features, define AI-driven product capabilities, and shape the product roadmap

- Drive rapid prototyping and iterative development cycles - build fast, validate fast

- Define evaluation metrics for AI models and systems - accuracy, latency, cost, reliability

Engineering & Technical Leadership:

- Build and maintain FastAPI-based backend services with clean, scalable architecture

- Work with PostgreSQL and Redis for data persistence, caching, and real-time workloads

- Manage and optimize AWS infrastructure - EC2, S3, RDS, Lambda, ECS, and related services

- Build and maintain CI/CD pipelines - GitHub Actions, CodePipeline or equivalent

- Contribute to frontend integration with AI APIs - ensuring seamless UX for AI-driven features

- Maintain documentation, code quality standards, and engineering best practices across the AI stack

Team Building & Mentorship:

- Lead and mentor a team of AI interns and junior engineers - assign tasks, review work, provide feedback

- Hire and build the AI team as the company scales - define roles, interview, and onboard

- Foster a culture of experimentation, ownership, and rapid learning

WHAT WE ARE LOOKING FOR

Must-Have Experience:

- 10-12 years of hands-on experience in AI/ML engineering - not just research, but production systems

- Proven experience in LLM application development - prompt engineering, fine-tuning, RAG, agents

- Strong experience in manufacturing domain - understanding of factory operations, OT systems, industrial IoT

- Hands-on knowledge of OT environments - OPC-UA, MQTT, Modbus, SCADA, PLC integration

- Experience with enterprise IT systems - ERP, MES, CMMS, HRMS, or banking/BFSI platforms

- Proficiency in Python - clean, production-quality code

- Hands-on with FastAPI - building RESTful and async APIs

- Strong SQL skills - PostgreSQL preferred; Redis for caching and queuing

- AWS infrastructure experience - hands-on with core services and cost management

- CI/CD experience - building and maintaining deployment pipelines

- Understanding of vector databases and semantic search architectures

- Time-series data processing experience - sensor data, telemetry, industrial signals

Strong Advantage:

- Experience with Agentic AI frameworks - LangGraph, CrewAI, AutoGen, or custom agent architectures

- Experience with BFSI / banking AI use cases

- Prior experience at an early-stage startup or as a technical co-founder

- Knowledge of edge computing and on-premise AI deployment in industrial settings

- Frontend awareness - React or similar; ability to integrate AI APIs with UI components

- Experience with MLOps - model versioning, experiment tracking, monitoring (MLflow, W&B, etc.)

Who You Are - The Mindset We Need

- You have a co-founder mindset - you take ownership, think long-term, and act like it is your company

- You are comfortable with ambiguity - early-stage means building the plane while flying it

- You lead by example - you do not just direct, you ship

- You are a strong communicator - can explain complex AI concepts to business stakeholders

- You are hungry to build something that matters - not just another AI feature, but transformative AI products