Job Title - Decision Science Practitioner Senior Analyst

Management Level: Sr. Analyst (Level 10)

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: 4+ 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 hands-on Decision Science Practitioner Senior Analyst to design and deliver Generative AI, Agentic AI, machine learning, and analytics solutions for Consumer Tech, Enterprise Tech, and Semiconductor clients.

The Senior Analyst will work closely with client stakeholders and cross-functional teams to build AI-powered applications, agent workflows, retrieval systems, and analytics solutions. The role requires strong technical execution, problem-solving, and the ability to independently own workstreams while mentoring junior team members.

Key Responsibilities

Generative AI, Agentic AI and RAG

Design and develop LLM-powered applications, assistants, and agent workflows using modern orchestration frameworks and enterprise integrations.
Build and optimize RAG solutions using embeddings, metadata, vector search, and enterprise knowledge repositories.
Develop agent workflows incorporating tool calling, memory, structured outputs, and multi-step reasoning patterns.
Contribute to agent orchestration using LangGraph or similar frameworks.
Evaluate AI applications using defined quality metrics such as relevance, latency, and reliability.
Investigate application behavior using logs, traces, and monitoring tools to improve performance and user experience.
Implement Responsible AI practices, security controls, guardrails, and human-in-the-loop review mechanisms.

Cloud Platform Expertise

Develop and deploy AI solutions on Azure and/or AWS using managed AI, data, and application services.
Support secure deployment, monitoring, model governance, credential management, and operational readiness.
Collaborate with platform and engineering teams to ensure scalable and reliable AI application deployment.

AI Engineering and Deployment

Build Python-based AI services and REST API integrations connecting enterprise systems, data sources, and AI applications.
Apply software engineering best practices including Git, code reviews, modular development, testing, documentation, and CI/CD.
Participate in solution design, technical estimation, troubleshooting, and performance optimization activities.
Guide Analysts and Associates on implementation approaches, coding standards, and delivery practices.
undefinedTechnical SkillsProgramming and APIs: Python, SQL, JSON, REST APIs, object-oriented programming, and software engineering best practices.GenAI and agents: Hands-on experience building LLM applications, agent workflows, RAG pipelines, prompt engineering, tool calling, and evaluation approaches.Retrieval and Knowledge Systems: Embeddings, vector search, enterprise document ingestion, metadata management, and familiarity with vector databases or enterprise search platforms.Cloud Platforms: Hands-on experience with Azure and/or AWS for AI, analytics, and application deployment.Preferred SkillsExperience with LangGraph, LangChain, LlamaIndex, AutoGen, CrewAI, or similar frameworks.Exposure to MCP, Agent-to-Agent (A2A) communication, GraphRAG, agent memory, or multimodal AI applications.Experience with evaluation, observability, tracing, monitoring, and AI application quality measurement.Understanding of Docker, CI/CD pipelines, MLOps, or cloud-native deployment patterns.Experience delivering analytics, AI, or decision science solutions in marketing, sales, customer experience, supply chain, or operations domains.Strong communication, analytical problem-solving, and stakeholder management skills.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

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