16 hours ago
Hyderābād, IndiaSenior
Responsibilities
- Design and build LLM application components including prompts, tools, agents, orchestration flows, memory and context handling, retrieval pipelines, and evaluation harnesses.
- Build data-grounded agentic applications on Databricks using RAG, Delta tables, Vector Search, MLflow, Model Serving, and Unity Catalog.
- Implement ingestion, parsing, chunking, enrichment, embeddings, vector search, and retrieval workflows for structured and unstructured enterprise content.
- Engineer safety and control components including PII detection and redaction, 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, maintainable software components.
- Create component designs, integration specifications, deployment runbooks, evaluation results, and reusable engineering patterns.
Requirements
- A bachelor's degree in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline is required.
- At least 5 years of software, data, or AI engineering experience is required; the posting also describes a 7+ year experience profile involving cloud-native architecture and GenAI delivery.
- Experience must include cloud-native engineering and delivery in GenAI, LLM, NLP, or agentic AI.
- Hands-on Python coding experience and strong knowledge of APIs, distributed systems, testing, observability, and secure SDLC practices are required.
- Experience with Databricks Mosaic AI, Model Serving, Agent Framework, MLflow tracing and evaluation, Vector Search, Unity Catalog, Delta Lake, Lakehouse Monitoring, Feature Store, Workflows, Jobs, notebooks, and Model Training is required.
- Experience delivering AI/ML or data products in an industry domain such as financial services, healthcare, manufacturing, retail, telecom, or life sciences is required.
- Knowledge of RAG, function and tool calling, agent orchestration, model invocation, prompt engineering, embeddings, vector databases, evaluation metrics, deployment, monitoring, and production AI controls is required.
- Experience with Git-based development, automated testing, CI/CD pipelines, infrastructure-as-code, and agile delivery in client-facing environments is required.
- Preferred qualifications include Databricks certifications, Spark or PySpark, Delta Live Tables, LangGraph, LangChain, model fine-tuning, lakehouse optimization, LlamaIndex, Haystack, MLflow, FastAPI, Docker, Kubernetes, Responsible AI, model risk management, synthetic data, human-in-the-loop review, A/B testing, and GenAI cost optimization.
Tech Stack
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.