17 hours ago
Hyderābād, IndiaSenior
Responsibilities
- Design and build LLM application components such as prompts, tools, agents, orchestration flows, memory and context handling, retrieval pipelines, and evaluation harnesses.
- Build data-grounded agentic applications on Databricks using Delta tables, Vector Search, governed features, 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 capabilities 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.
- 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 software, data, or AI engineering experience, including cloud-native engineering and GenAI, LLM, NLP, or agentic AI delivery; the posting also lists a 7+ year experience profile with additional architecture experience.
- Hands-on Python coding experience and strong understanding of APIs, distributed systems, testing, observability, secure SDLC practices, Git-based development, CI/CD, infrastructure-as-code, and agile delivery.
- Hands-on 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.
- Understanding of LLM application architecture, RAG, function and tool calling, agent orchestration, model invocation, prompt engineering, embeddings, vector databases, and evaluation metrics.
- Experience implementing traditional ML and GenAI components across ingestion, feature and data preparation, model integration, deployment, monitoring, and continuous improvement.
- Experience delivering AI/ML or data products in at least one domain such as financial services, healthcare, manufacturing, retail, telecom, or life sciences.
- Preferred qualifications include Databricks certifications, Spark or PySpark, Delta Live Tables, LangGraph or 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.