3 days ago
Bengaluru, IndiaSenior
Responsibilities
- Design and develop LLM-powered applications, assistants, agent workflows, and enterprise integrations.
- Build and optimize RAG solutions using embeddings, metadata, vector search, and enterprise knowledge repositories.
- Develop agent workflows with tool calling, memory, structured outputs, multi-step reasoning, and multi-agent systems.
- Contribute to agent orchestration using LangGraph or similar frameworks and evaluate AI applications using relevance, latency, reliability, and other quality metrics.
- Investigate application behavior through logs, traces, and monitoring tools and improve performance and user experience.
- Implement Responsible AI practices, security controls, guardrails, and human-in-the-loop review mechanisms.
- Develop and deploy AI solutions on Azure and/or AWS using managed AI, data, and application services.
- Build Python-based AI services and REST API integrations connecting enterprise systems, data sources, and AI applications.
- Participate in solution design, technical estimation, troubleshooting, performance optimization, testing, documentation, and CI/CD activities.
- Independently own workstreams, collaborate with clients and engineering teams, and mentor Analysts and Associates on implementation and coding practices.
Requirements
- At least 4 years of hands-on experience in AI/ML, data science, Generative AI, or related engineering.
- Bachelor's or Master's degree in Computer Science, AI, Data Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline.
- Hands-on proficiency with Python, SQL, Generative AI/LLMs, Agentic AI, RAG, API integration, cloud AI platforms, and LangGraph or similar frameworks.
- Experience with LLM applications, agent workflows, RAG pipelines, prompt engineering, tool calling, evaluation approaches, embeddings, vector search, document ingestion, and metadata management.
- Experience with Azure and/or AWS for AI, analytics, and application deployment.
- Preferred experience with LangGraph, LangChain, LlamaIndex, AutoGen, CrewAI, MCP, Agent-to-Agent communication, GraphRAG, agent memory, multimodal AI, observability, tracing, monitoring, Docker, CI/CD, MLOps, or cloud-native deployment.
- Strong communication, analytical problem-solving, stakeholder management, and mentoring skills.
- Ability to explain the business problem, individual contribution, and testing approach for hands-on AI solutions.
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.