3 days ago
Bengaluru, IndiaSenior
Responsibilities
- Design and build LLM application components, including prompts, tools, agents, orchestration flows, memory and context handling, retrieval pipelines, and evaluation harnesses.
- Design AWS agent workflows using Bedrock and serverless patterns, integrate enterprise APIs, and build secure RAG over S3, OpenSearch, and Knowledge Bases.
- Implement ingestion, parsing, chunking, enrichment, embeddings, vector search, and retrieval workflows for structured and unstructured enterprise content.
- Engineer PII controls, prompt-injection defenses, content filters, guardrails, authentication, authorization, lineage, and audit logging.
- Collaborate with architects, data engineers, product owners, and security stakeholders to deliver tested, observable, and maintainable software components.
- Maintain component designs, integration specifications, deployment runbooks, evaluation results, and reusable engineering patterns.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- At least 5 years of experience is required, with qualifications describing 5+ or 7+ years of software, data, or AI engineering experience depending on the profile.
- Experience must include cloud-native engineering or architecture and GenAI, LLM, NLP, or agentic AI delivery.
- Hands-on Python coding experience and strong knowledge of APIs, distributed systems, testing, observability, and secure SDLC practices.
- Experience delivering AI/ML or data products in banking, insurance, healthcare, retail, telecom, or capital markets.
- Hands-on experience with AWS AI, serverless, data, security, monitoring, and infrastructure services listed in the posting.
- Knowledge of LLM application architecture, RAG, tool calling, agent orchestration, prompt engineering, embeddings, vector databases, and evaluation metrics.
- Experience with data ingestion, model integration, deployment, monitoring, continuous improvement, Git-based development, automated testing, CI/CD, infrastructure-as-code, and client-facing delivery.
- Preferred qualifications include AWS Solutions Architect or Machine Learning Specialty certification, CDK or Terraform, EKS, Amazon Q, responsible AI controls, FinOps, and frameworks such as LangChain, LangGraph, LlamaIndex, Haystack, MLflow, FastAPI, Docker, and Kubernetes.
Categories
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.