JD - PPE

Requirements:

Skill/Operating Group

Product Platform Engineering, Industry X, Capability Network

Position

AI Transformation Lead (PO/BA/Project Manager/SME)

Location

India

Key Industries of Work

CMT, Lifesciences, Healthcare, Banking Capital Markets, Finance Insurance, CGS, Retail, Travel, Energy / Utilities

Experience

5+ years in consulting or product management, with demonstrable experience in leading or contributing to AI/ML or Gen AI/Agentic AI projects

Academic Background

MBA from Tier 1 Colleges

Job Summary

As an AI Expert, you will be at the forefront of the AI revolution. You will leverage your deep functional expertise and emerging AI knowledge to guide global clients in harnessing the power of Gen AI and Agentic AI. You will act as a strategic advisor, translating complex AI capabilities into tangible business value, defining transformative roadmaps, and managing the delivery of AI-powered solutions across diverse industries. This is a non-technical, client-facing role focused on strategy, product management and business transformation.

Roles and Responsibilities

- Advise clients on AI strategy, identifying high-impact use cases and building actionable adoption roadmaps.

- Manage the end-to-end agile delivery of AI solutions, translating business needs into successful products.

- Act as the primary bridge between business stakeholders and technical teams to ensure AI solutions meet strategic goals.

- Champion change management to drive user adoption of AI tools and foster a culture of innovation.

- Serve as the functional expert on AI platforms, tools, and responsible AI principles to guide client decision-making.

Required Skills Experience

- Consulting Acumen: Proven experience in client-facing roles such as Program Manager, Project Manager, Business Analyst, Product Manager, or Agile Coach.

- AI Project Experience: Demonstrable experience in defining, managing, or delivering projects with a significant AI or Generative AI component.

- AI Knowledge (Functional):

- Solid understanding of the Generative AI landscape, including key concepts like LLMs, prompt engineering, and their business applications.

- Familiarity with major AI platforms and their capabilities (e.g., Microsoft Azure AI, Google Cloud AI, AWS AI services).

- Awareness of how AI is being integrated into enterprise platforms (e.g., ServiceNow, Salesforce, SAP).

- Core Consulting Skills:

- Exceptional ability to gather, analyze, and translate business requirements into actionable plans.

- Outstanding communication, presentation, and stakeholder management skills, with the ability to influence C-level executives.

- Good to Have:

- Knowledge of AI governance, risk management, and ethical frameworks.

- Certifications in Agile (e.g., SAFe, CSPO, CSM) or AI platforms.

JD - DERD

Requirements:

Skill/Operating Group

Production Operations, Industry X, Capability Network

Position

Consultant

Location

India

Key Industries of Work

Consumer Goods Services (CGS), Automotive, Industrial Equipment, Med-Tech, Aerospace Defense, Hi-Tech, Lifesciences etc

Experience

6+ years in consulting or product management, with demonstrable experience in leading or contributing to AI/ML or Gen AI/Agentic AI projects

Academic Background

BE/B.Tech from IIT/NIT/Tier-1 institutes
MBA from Tier 1 Colleges

Job Summary

You will be at the forefront of the AI revolution. You will leverage your deep functional expertise and emerging AI domain knowledge to guide global clients in harnessing the power of Gen AI and Agentic AI. You will act as a strategic advisor, translating complex AI capabilities into tangible business value, defining transformative roadmaps, and managing the delivery of AI-powered solutions across diverse industries.



This is a non-technical, client-facing role focused on engineering and RD digital transformation strategy.

Roles and Responsibilities

MBA or equivalent management qualification combined with an engineering or technology foundation.

- Aligned with the roles responsibilities of one of the capabilities within CoE, being recruited for.

- Advise clients on AI strategy, identifying high-impact use cases and building actionable adoption roadmaps.
- Manage the end-to-end agile delivery of AI solutions, translating business needs into successful products.
- Act as the primary bridge between business stakeholders and technical teams to ensure AI solutions meet strategic goals.
- Champion change management to drive user adoption of AI tools and foster a culture of innovation.
- Serve as the functional expert on AI platforms and tools to guide client decision-making.

Key Competencies

Must Have:

- Aligned with the skills required for one of the capabilities with CoE, being recruited for.
- Consulting Acumen: Proven experience in client-facing roles such as Program Manager, Project Manager or Business Analyst.
- AI Project Experience: Demonstrable experience in defining, managing, or delivering projects with a significant AI or Generative AI component.
- AI Knowledge (Functional):
- Solid understanding of the Generative AI landscape, including key concepts like LLMs, prompt engineering, and their business applications.
- Familiarity with major AI platforms and their capabilities (e.g., Microsoft Azure AI, Google Cloud AI, AWS AI services).
- Awareness of how AI is being integrated into enterprise platforms (e.g., PLM, SAP).

- Core Consulting Skills:

- Exceptional ability to gather, analyze, and translate business requirements into actionable plans.
- Outstanding communication, presentation, and stakeholder management skills, with the ability to influence C-level executives.

Good to Have:

- - Knowledge of AI governance, risk management, and ethical frameworks.
- Certifications in Agile (e.g., SAFe, CSPO, CSM) or AI platforms.

JD - IAM Industrial AI Analyst - Maintenance Reliability

Experience: 2 4 years
Location focus: India / Argentina / Kuala Lumpur
Reporting: Reports to Manager / Senior Manager (no direct reports)
Team context: Embedded within Strategy Consulting; works closely with functional consultants, client teams, and data scientists.

Role Summary

We are hiring an Analyst to join our Strategy Consulting practice focused on Asset Reliability, Maintenance Operational Excellence. This is a client-facing, hands-on data and AI role where you will combine technical analytics (data engineering, modelling, AI development) with business-facing capabilities (value-case development, structured communication, and presentations).

You will work on AI and analytics use cases that improve asset reliability, predictive maintenance, and operational performance including applications of LLMs, AI agents and copilots within industrial workflows.
The role requires strong Python skills, practical knowledge of data architectures and pipelines, and exposure to maintenance / predictive-maintenance use cases in manufacturing or related industries.

Key Responsibilities

- Partner with Maintenance Reliability stakeholders and internal consulting leads to identify and prioritize high-impact AI/analytics use cases.





- Identify and develop AI use cases across asset management areas (reliability, predictive analytics, maintenance optimization), including opportunities for AI agents and copilots to automate or augment workflows.

- Translate business problems into analytic problem statements and measurable value cases (e.g., cost avoidance, uptime improvement).

- Collect, clean, integrate and structure asset, maintenance and sensor data from EAM/CMMS, historians, IoT and PLC systems.

- Build and validate predictive maintenance and condition-monitoring models (time-series, anomaly detection, NLP, classification/regression etc.) using Python or any other platform.

- Implement end-to-end proof-of-concepts: data ingestion, feature engineering, model development, evaluation, deployment/hand-over to concerned teams.

- Produce impactful client deliverables: slide decks, technical notes, and demo presentations that articulate business impact and ROI.

- Demonstrate familiarity with responsible AI practices, data governance and industrial security considerations.

- Support change management and capability-building workshops with client teams and COE.

- Work within cross-functional teams (data engineers, domain SMEs, functional consultants) to move pilots toward scalable solutions.

- Support deployment and monitoring of models (MLOps) using tools such as MLflow or Airflow.

Must-have Qualifications Skills

- B.Tech / BE (mandatory). MBA or equivalent in analytics/management is preferred.

- 2 4 years experience in analytics / data science; experience in manufacturing, mining, chemicals, cement, energy or utilities is strongly preferred.

- Solid, production-grade proficiency in Python or similar (data wrangling, modelling, libraries such as pandas, scikit-learn, statsmodels, PyTorch/TensorFlow desirable).

- Robust understanding of data pipelines, ETL, and data architecture patterns.

- Practical experience with time-series modelling, anomaly detection, NLP, predictive maintenance methods, condition monitoring, and related modelling and analytics.

- Familiarity with industrial data sources: SAP PM / IBM Maximo / other CMMS, historians (OSI PI / equivalent), IoT sensor data.

- AI/ML Techniques: time-series forecasting, anomaly detection, NLP, predictive modeling.

- Deployment MLOps: experience with model deployment, monitoring, lifecycle management (MLflow, Airflow, etc.), including cloud-based environments (Azure, AWS, GCP, Databricks).

- GenAI / LLM exposure: understanding of prompt engineering, retrieval-augmented generation (RAG), AI agents frameworks understanding.

- Ability to build persuasive value cases and present technical results to senior business stakeholders.

- Excellent written and verbal communication, structured problem solving, and ability to work in cross-functional teams.

- English Fluency (mandatory)

Nice-to-have

- Experience with cloud/data platforms (Azure, AWS, GCP), Databricks or equivalent (beyond basic familiarity).

- Experience with visualization tools (Power BI, Tableau, QlikView).

- Knowledge of reliability engineering techniques (FMEA, RCA, RCM).

- Certifications in cloud platforms or reliability engineering.

Behavioral Competencies

- Client-facing, professional consulting demeanor (formal presentation and reporting).

- Curious, pragmatic, outcome-focused; comfortable working in ambiguous and challenging environments.

- Team player who can collaborate with both technical and non-technical stakeholders.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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