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S&C Global Network - AI - Hi Tech - Data Science Consultant

Pay
Pay not listed
Work setting
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design agent architectures involving orchestration, memory, tool calling, enterprise integration, and human-in-the-loop controls.

  • Design and develop AI applications, APIs, and integrations with enterprise systems and business workflows.

  • Design and deploy machine learning, predictive analytics, recommendation, forecasting, and optimization solutions.

From the employer’s posting
Architect and develop production-grade LLM applications, AI assistants, agentic workflows, and RAG solutions. Design agent architectures involving orchestration, memory, tool calling, enterprise integration, and human-in-the-loop controls. Optimize retrieval systems using embeddings, metadata, vector search, hybrid search, and enterprise knowledge repositories.
AI Engineering and Cloud Platforms Design and develop AI applications, APIs, and integrations with enterprise systems and business workflows. Lead technical implementation using Python, modern AI frameworks, and cloud-native services on Azure and/or AWS.
Data Science and Analytics Design and deploy machine learning, predictive analytics, recommendation, forecasting, and optimization solutions. Integrate traditional ML and statistical models into GenAI and agentic AI workflows where appropriate.

What you’ll bring

All qualifications

Core experience

  • Experience: 6+ years of hands-on work in AI/ML, data science, Generative AI or related engineering.

Preferred experience

  • Experience in Consumer Tech, Enterprise Tech, Semiconductor, or other Hi-Tech industries.
Qualification wording
Experience: 6+ years of hands-on work in AI/ML, data science, Generative AI or related engineering.
Experience in Consumer Tech, Enterprise Tech, Semiconductor, or other Hi-Tech industries.
Education & alternatives
Experience: 6+ years in AI/ML, data science, GenAI or related engineering Educational Qualification: Bachelor's or Master's degree in Computer Science, AI, Data Science, Statistics, Applied Mathematics, Engineering or a related field Job Summary:
Experience: 6+ years of hands-on work in AI/ML, data science, Generative AI or related engineering. Education: Bachelor's or Master's degree in a relevant quantitative or engineering discipline. About Accenture

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale.

In the employer’s words · Read in context

Apply at Accenture

Posting record

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Status in our records
Live
First seen by us
Sep 25, 202649 days ago
Recorded sightings
61
Last seen by us
Nov 12, 2026
Reposted
once since Aug 18, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

Time since we first saw it

Day 49

Similar jobs usually come down between day 4 and day 77.

Well past Accenture’s usual: its jobs come down by about day 1.

From 51 similar postings that came down, and 2,606 of Accenture’s. Coming down is not always a hire.

Accenture is hiring

250 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Takes jobs down quickly
  • 14% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Docker
  • Kubernetes
  • PyTorch
  • scikit-learn
  • TensorFlow
Where the posting names them
Location: Bengaluru (preferred) / Kolkata / Gurugram Must have skills: Python, SQL, Generative AI/LLMs, Agentic AI, RAG, API integration, Cloud AI platforms, LangGraph or similar frameworks, MCP, multi-agent systems, A2A Experience: 6+ years in AI/ML, data science, GenAI or related engineering
- Design and develop AI applications, APIs, and integrations with enterprise systems and business workflows. - Lead technical implementation using Python, modern AI frameworks, and cloud-native services on Azure and/or AWS. - Define deployment architectures, CI/CD approaches, security standards, monitoring, and operational readiness.
Technical Skills Programming & Engineering: Python, SQL, APIs, software engineering best practices, CI/CD, Git. Generative AI & Agents: LLM applications, RAG, agent workflows, prompt engineering, tool calling, evaluation frameworks.
AI Engineering: LangGraph, LangChain, Semantic Kernel, LlamaIndex, AutoGen, CrewAI, or similar frameworks. Cloud Platforms: Azure and/or AWS AI, data, security, deployment, and monitoring services. Machine Learning: scikit-learn, PyTorch, TensorFlow, predictive analytics, model evaluation, and deployment.
- AI observability, evaluation, governance, and Responsible AI practices. - Docker, Kubernetes, MLOps, and cloud-native deployment architectures. - Experience in Consumer Tech, Enterprise Tech, Semiconductor, or other Hi-Tech industries.
Cloud Platforms: Azure and/or AWS AI, data, security, deployment, and monitoring services. Machine Learning: scikit-learn, PyTorch, TensorFlow, predictive analytics, model evaluation, and deployment. Solution Architecture: End-to-end AI solution design, enterprise integration, security, scalability, and performance optimization.

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Has Accenture posted this job before?

Yes. We’ve followed one other S&C Global Network - AI - Hi Tech - Data Science Consultant job there since August 2026. It is still up.

  1. PuneStill up after 87 days, first seen Aug 18
  2. This jobUp 49 days so far, first seen Sep 25

About Accenture

People
About 814,000 in 2026, up 4% from the year before.Annual report (SEC Form 10-K)
Company
Listed as ACN.
H-1B visas
294 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Layoff notices
Notices this year and last cover 85 people. The latest was filed May 14, 2025.State WARN notices

Demand for AI Engineer roles

New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.

Weekly new AI Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 7, the most 65, and the latest week had 65.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under AI Engineer, by the work the posting describes.

AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.

Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.

An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.

Job description

View original posting ↗

Job Title - Decision Science Practitioner Consultant

Management Level: Consultant (Level 9)

Location: Bengaluru (preferred) / Kolkata / Gurugram

Must have skills: Python, SQL, Generative AI/LLMs, Agentic AI, RAG, API integration, Cloud AI platforms, LangGraph or similar frameworks, MCP, multi-agent systems, A2A

Experience: 6+ years in AI/ML, data science, GenAI or related engineering

Educational Qualification: Bachelor's or Master's degree in Computer Science, AI, Data Science, Statistics, Applied Mathematics, Engineering or a related field

Job Summary:

We are seeking a technically strong AI Consultant to lead the design and delivery of Generative AI, Agentic AI, machine learning, and analytics solutions for Consumer Tech, Enterprise Tech, and Semiconductor clients.

The role combines hands-on technical leadership, solution architecture, team leadership, and client delivery management. Candidates should be able to translate business requirements into scalable AI solutions while guiding teams through implementation and deployment.

Key Responsibilities

Generative AI, Agentic AI and Knowledge Systems

  • Architect and develop production-grade LLM applications, AI assistants, agentic workflows, and RAG solutions.
  • Design agent architectures involving orchestration, memory, tool calling, enterprise integration, and human-in-the-loop controls.
  • Optimize retrieval systems using embeddings, metadata, vector search, hybrid search, and enterprise knowledge repositories.
  • Lead evaluation of AI applications for relevance, reliability, latency, safety, and business outcomes.
  • Implement Responsible AI practices, security controls, guardrails, observability, and monitoring frameworks.

AI Engineering and Cloud Platforms

  • Design and develop AI applications, APIs, and integrations with enterprise systems and business workflows.
  • Lead technical implementation using Python, modern AI frameworks, and cloud-native services on Azure and/or AWS.
  • Define deployment architectures, CI/CD approaches, security standards, monitoring, and operational readiness.
  • Drive code reviews, technical standards, testing, debugging, and performance optimization

Data Science and Analytics

  • Design and deploy machine learning, predictive analytics, recommendation, forecasting, and optimization solutions.
  • Integrate traditional ML and statistical models into GenAI and agentic AI workflows where appropriate.
  • Apply advanced analytics techniques to solve business challenges across sales, marketing, customer support, and supply chain domains.

Technical Leadership and Client Delivery

  • Lead AI and analytics workstreams from solution design through deployment and stabilization.
  • Translate business problems into scalable technical solutions and architecture decisions.
  • Mentor junior practitioners and provide technical guidance across engineering and delivery teams.
  • Manage client stakeholders, communicate technical recommendations, and support solution shaping activities.
  • Contribute to proposals, estimations, technical workshops, demos, and reusable AI assets.

Technical Skills

Programming & Engineering: Python, SQL, APIs, software engineering best practices, CI/CD, Git.

Generative AI & Agents: LLM applications, RAG, agent workflows, prompt engineering, tool calling, evaluation frameworks.

AI Engineering: LangGraph, LangChain, Semantic Kernel, LlamaIndex, AutoGen, CrewAI, or similar frameworks.

Cloud Platforms: Azure and/or AWS AI, data, security, deployment, and monitoring services.

Machine Learning: scikit-learn, PyTorch, TensorFlow, predictive analytics, model evaluation, and deployment.

Solution Architecture: End-to-end AI solution design, enterprise integration, security, scalability, and performance optimization.

Preferred Skills

  • MCP, Agent-to-Agent (A2A) communication, GraphRAG, agent memory, and multimodal AI.
  • AI observability, evaluation, governance, and Responsible AI practices.
  • Docker, Kubernetes, MLOps, and cloud-native deployment architectures.
  • Experience in Consumer Tech, Enterprise Tech, Semiconductor, or other Hi-Tech industries.
  • Strong consulting, stakeholder management, and technical leadership capabilities.

Additional Information:

The position is based in Bengaluru (preferred), Kolkata or Gurugram. Candidates should be able to demonstrate hands-on contributions to AI solutions and explain the business problem, their contribution and how the solution was tested.

About Our Company | Accenture

Required Qualifications

Experience: 6+ years of hands-on work in AI/ML, data science, Generative AI or related engineering.

Education: Bachelor's or Master's degree in a relevant quantitative or engineering discipline.

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

Visit us at www.accenture.com 

Equal Employment Opportunity Statement


We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.

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- Design agent architectures involving orchestration, memory, tool calling, enterprise integration, and human-in-the-loop controls. - Optimize retrieval systems using embeddings, metadata, vector search, hybrid search, and enterprise knowledge repositories. - Lead evaluation of AI applications for relevance, reliability, latency, safety, and business outcomes.
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