20 hours ago
Pune, IndiaSenior
Responsibilities
- Design and build LLM application components such as prompts, tools, agents, orchestration flows, memory and context handling, retrieval pipelines, and evaluation harnesses.
- Develop Cortex-powered LLM applications and agents within Snowflake, including RAG, document intelligence, Streamlit and Snowpark applications, and enterprise AI platform integrations.
- Implement data ingestion, parsing, chunking, enrichment, embeddings, vector search, and retrieval workflows for structured and unstructured 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 convert designs into tested, observable, and maintainable software components.
- Maintain component designs, integration specifications, deployment runbooks, evaluation results, and reusable engineering patterns.
- Serve as a hands-on technical or engineering lead by contributing code, design decisions, and production-quality implementations.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- At least 7.5 years of professional experience.
- Hands-on Python coding experience and strong understanding of APIs, distributed systems, CI/CD, testing, observability, and secure SDLC practices.
- Experience delivering AI/ML or data products in an industry such as banking, insurance, retail, healthcare, travel, logistics, or telecommunications.
- Hands-on experience with Snowflake Cortex AI, Cortex Agents, Cortex Search, Cortex Analyst, Cortex AI Functions or LLM Functions, Snowpark, Streamlit in Snowflake, Dynamic Tables, Tasks, Streams, Snowflake ML, RBAC, masking policies, and observability.
- Understanding of LLM application architecture, including RAG, function and tool calling, agent orchestration, model invocation, prompt engineering, embeddings, vector databases, and evaluation metrics.
- Ability to implement traditional ML and GenAI components across ingestion, data preparation, model integration, deployment, monitoring, and continuous improvement.
- Knowledge of security, privacy, governance, performance, scalability, reliability, and cost controls for production AI systems.
- Experience with Git-based development, automated testing, CI/CD pipelines, infrastructure-as-code, and agile delivery in client-facing environments.
- Preferred experience with SnowPro Advanced Architect or Data Engineer certification, Snowpark Python, Streamlit, semantic models, dbt, Native Apps, Snowflake governance, data sharing, and cost or performance tuning.
- Preferred exposure to LangChain, LangGraph, 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.