Project Role: Data Science Practitioner Project Role Description:

Formulating, design and deliver AI/ML-based decision-making frameworks and models for business outcomes. Measure and justify AI/ML based solution values.

Must have skills:

Data Science

Valuable to have skills:

NA

Minimum 5 year(s) of experience is required

Educational Qualification:

15 years full time education

AI Engineer / Data Scientist - NLP & Generative AI Experience: 6-7 years

Location: India

Role Summary Build and productionize NLP and generative AI capabilities - from classical NLP through LLM-based agentic workflows - for real-time, high-scale enterprise applications, with a focus on prompt engineering, RAG, and conversational AI experiences.

Key Responsibilities

- Design, fine-tune, and optimize prompts for production LLM features (summarization, classification, sentiment, Q&A;, translation, knowledge-gap analysis)
- Build agentic workflows (e.g., CrewAI, LangChain, LangGraph, or equivalent) to orchestrate RAG pipelines and multi-step evaluation/validation tasks
- Apply classical NLP techniques (clustering, sentiment analysis, NER, topic modeling, text classification) using transformer models alongside LLMs where appropriate
- Develop and deploy real-time inference APIs to serve AI features to production applications at scale
- Integrate speech-to-text and text-to-speech capabilities for conversational/simulation use cases
- Build monitoring/analytics pipelines for productivity and quality metrics derived from AI outputs
- Iterate on model performance through hyperparameter tuning, feedback loops, and evaluation against production data
- Work across open-source and hosted LLMs, selecting the right model/deployment for cost, latency, and accuracy needs




- Partner with data engineering on ingestion/synchronization pipelines across relational and vector data stores
- Present KPI metrics, model performance, and insights to business stakeholders via dashboards

Required Skills & Experience

- 6 years in NLP / data science / AI engineering with production deployment experience
- Strong Python experience serving ML/AI models via production APIs
- NLP fundamentals: text classification, NER, clustering, topic modeling, summarization, sentiment analysis
- Transformer model experience: BERT/RoBERTa/T5/BART or equivalent
- LLM and agentic tooling: prompt engineering, RAG, agentic frameworks (e.g., CrewAI, LangChain, LangGraph), and LLM APIs (e.g., GPT, Claude, or open-source models)
- Classical ML: supervised/unsupervised algorithms and evaluation methodology
- Hands-on depth with Azure AI and compute services - Azure AI Foundry, Azure Function Apps, Azure Logic Apps - or equivalent AWS/GCP AI and serverless stacks
- SQL databases plus exposure to a vector store

Preferred

- Knowledge graph / graph-based retrieval techniques for RAG (e.g., Neo4j or equivalent)
- Production deployment experience across multiple major cloud platforms (AWS, Azure, and GCP) - spanning AI/ML services, managed databases, and serverless compute
- Speech-to-text/text-to-speech integration experience for conversational AI use cases
- Experience with no-code/low-code platforms (e.g., Microsoft Power Platform, Copilot Studio, or equivalent) for rapid agent/bot prototyping
- Dashboarding (Power BI/Tableau)
- Exposure to healthcare or other regulated-data domains

Education Bachelor's/master's in data science, Computer Science, Statistics, or related field

Locations:

Job No. ATCI-5748853-S2066938 | Hyderabad | Required Skill: Data Science

📌 Data Science Practitioner (India)
🏢 Accenture
📍 India