Principal AI/ML Architect

Tao Digital Solutions Inc.; Hyderabad; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

TAO Digital Solutions seeks an experienced AI/ML architect with 12+ years in software and data science, including 6+ years in AI/ML and 3+ years leading production AI architectures for asset-intensive industries. The role focuses on designing target-state architectures and roadmaps for complex telemetry, time-series, and IoT data across industries.

Candidates should show hands-on delivery from PoC to production, strong communication with engineering and operations teams, and a track record of

Qualifications

• 12+ years in software, data science, ML engineering, or related tech roles.
• 6+ years building and deploying AI/ML solutions; 3+ years owning architecture in production.
• Experience leading production AI architecture in asset-intensive environments.
• Demonstrable work with high-volume time-series, telemetry, or machine-generated data.
• Evidence of taking AI from PoC to production and operations.
• Strong architecture & design communication; ADRs, non-functional requirements.
• Bachelors or Masters in CS/AI/DS or related field; advanced degree preferred.
• Strong stakeholder skills with engineering leaders, maintenance, IT/OT, cybersecurity, execs.

Responsibilities

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Skills

AI/ML leadership

Production AI architectures

Industrial analytics

Stakeholder management

Time-series data

Architecture & design

Education

Bachelors/Master in CS/AI/DS

Tools

Azure OpenAI

AWS Bedrock

Vertex AI

LangChain

Semantic Kernel

Pinecone

Weaviate

Milvus

OpenSearch

Neo4j

Kafka

MQTT

OPC-UA

Docker

Kubernetes

IoT platforms

IBM Maximo

SAP PM/EAM

ServiceNow

AVEVA PI

OSIsoft

SCADA

MES/MOM

PLM/MRO

Grafana

Power BI

Tableau

Job description

Dear Folks,

We have an exciting opportunity for the above role @ TAO Digital Solutions (www.taodigitalsolutions.com)

Experience

12 to 18+ years overall. Candidate should have min 6+ years in AI/ML; 3+ years leading production AI architecture in asset-intensive environments

Pref Industry

Telecommunications; Energy / Oil & Gas; Automotive / Manufacturing; Aerospace / Aviation

Preferred platform / tool exposure

• GenAI: Azure OpenAI / AI Foundry, AWS Bedrock, Google Vertex AI; LangGraph/LangChain/Semantic Kernel; vector databases such as Pinecone, Weaviate, Milvus, pgvector or OpenSearch; graph technology such as Neo4j is a plus.
• Industrial / edge: Kafka or equivalent event streaming; MQTT, OPC-UA; Docker/Kubernetes; AWS IoT Core/SiteWise/Greengrass/TwinMaker, Azure IoT Hub/IoT Edge/Digital Twins, or equivalent IIoT platforms.
• Operational systems: IBM Maximo, SAP PM/EAM, ServiceNow, AVEVA PI/OSIsoft historian, SCADA/DCS, MES/MOM; telecom OSS/BSS/NMS/service-assurance platforms; PLM/MRO systems where applicable.
• Observability / visualization: Grafana, Power BI/Tableau, cloud monitoring stacks; AI/model observability platforms are desirable.
• 12+ years in software, data science, ML engineering, industrial analytics or related technology roles, with clear progression into architecture/technical leadership.
• 6+ years building and deploying AI/ML solutions; at least 3 years owning architecture or technical leadership for production-grade AI programs.
• Demonstrable work with high-volume time-series, telemetry, event or machine-generated data and at least one asset-intensive industry.
• Evidence of taking AI from discovery/PoC through production and operationsnot only experimentation or notebooks.
• Strong architecture and design communication: can produce target-state architectures, integration patterns, ADRs, non-functional requirements, risk/assumption logs and implementation roadmaps.
• Bachelors or Master’s degree in Computer Science, AI/ML, Data Science, Electrical/Mechanical/Industrial/Aerospace Engineering, Applied Mathematics or related field. Advanced degree is preferred but equivalent industrial experience is acceptable.
• Strong stakeholder skills with engineering leaders, maintenance/reliability teams, operations, IT/OT, cybersecurity, product management and executive audiences.