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 Snowflake Cortex-powered LLM applications and agents, including RAG and document-intelligence solutions using Cortex Search and Cortex AI Functions.
- Build Streamlit and Snowpark applications within the Snowflake security perimeter and apply RBAC, masking, lineage, and monitoring controls.
- Implement ingestion, parsing, chunking, enrichment, embeddings, vector search, and retrieval workflows for structured and unstructured enterprise content.
- Engineer safety and control features 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, and maintainable software components.
- Maintain component designs, integration specifications, deployment runbooks, evaluation results, and reusable engineering patterns.
- Contribute code and technical decisions as a hands-on technical or engineering lead across client engagements.
Requirements
- At least 5 years of professional experience is required.
- Bachelor’s degree in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline is required.
- Hands-on coding experience with Python and strong understanding of APIs, distributed systems, CI/CD, testing, observability, and secure SDLC practices.
- Experience delivering AI/ML or data products in at least one domain 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 patterns 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 qualifications include SnowPro Advanced Architect or Data Engineer certification, Snowpark Python, Streamlit, semantic models, dbt, Native Apps, Snowflake governance, data sharing, and cost or performance tuning experience.
- Preferred experience includes 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.