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.
- Develop Cortex-powered LLM applications and agents within Snowflake, including Cortex Search, Cortex AI Functions, Streamlit/Snowpark applications, RBAC, masking, lineage, and monitoring.
- 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 convert designs into tested, observable, maintainable software components.
- Maintain 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 7.5 years of experience is required.
- Hands-on Python coding experience and strong understanding of APIs, distributed systems, testing, observability, and secure SDLC practices are required.
- Experience delivering AI/ML or data products in at least one domain such as banking, insurance, retail, healthcare, travel, logistics, or telecom is required.
- Hands-on experience with Snowflake Cortex AI, Cortex Agents, Cortex Search, Cortex Analyst, Cortex AI Functions/LLM Functions, Snowpark, Streamlit in Snowflake, Dynamic Tables, Tasks, Streams, Snowflake ML, RBAC, masking policies, and observability is required.
- Knowledge of LLM application architecture, RAG, tool calling, agent orchestration, model invocation, prompt engineering, embeddings, vector databases, and evaluation metrics is required.
- Experience implementing traditional ML and GenAI components across data preparation, model integration, deployment, monitoring, and continuous improvement is required.
- Practical knowledge of security, privacy, governance, performance, scalability, reliability, and cost controls for production AI systems 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 SnowPro Advanced Architect/Data Engineer or Snowflake ML exposure, Snowpark Python, Streamlit, semantic models, dbt, Native Apps, Snowflake governance, data sharing, and cost/performance tuning.
- Preferred experience includes LangChain, LangGraph, LlamaIndex, Haystack, MLflow, FastAPI, Docker, Kubernetes, Responsible AI, model risk management, synthetic data generation, 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.