EY GDS - Senior-AppSec-AI-Automation-Engineer
Ernst and Young25 days ago
Bengaluru, IndiaSenior
Responsibilities
- Design, develop, and optimize AI-driven automation solutions using LLMs, agent frameworks, and orchestration platforms.
- Own end-to-end implementation of solution components, including enterprise integrations and CI/CD pipeline integration.
- Optimize AI systems for latency, cost, accuracy, and scalability using techniques such as caching, batching, and prompt optimization.
- Develop and enhance RAG pipelines through chunking strategies, retrieval tuning, re-ranking, and embeddings optimization.
- Implement fine-tuning strategies, dataset preparation, prompt tuning, and model evaluation workflows.
- Build and productionize agentic systems using LangGraph, AutoGen, CrewAI, Semantic Kernel, or equivalent frameworks.
- Develop automated evaluation frameworks, benchmarking pipelines, and model performance metrics.
- Contribute to AI harness frameworks, reusable accelerators, and enterprise AI development standards.
- Lead small workstreams, client discussions, demonstrations, and proof-of-concept implementations.
- Mentor junior AI Automation Engineers and review their work for engineering quality and best practices.
- Collaborate with architects to translate high-level designs into scalable implementations.
- Apply secure coding, DevSecOps, and AI security practices, including protection against prompt injection, jailbreaks, data leakage, and model misuse.
Requirements
- Bachelor’s degree in computer science, engineering, AI/ML, cybersecurity, or a related field.
- 4–8 years of experience in software engineering, AI/ML, or automation engineering.
- Strong hands-on experience implementing and optimizing AI/LLM-based solutions.
- Strong proficiency in Python and exposure to JavaScript, TypeScript, or other programming languages.
- Experience with LLM tools, AI frameworks, cloud platforms, AI platforms, vector databases, observability and evaluation tools, DevOps and CI/CD tools, and prototyping environments.
- Knowledge of RAG optimization, prompt engineering, embeddings, model fine-tuning including LoRA/basic methods, evaluation frameworks, and agentic workflows.
- Experience working in client-facing consulting environments.
- Preferred cybersecurity experience in application security, offensive security, or AI/LLM-specific risks.
- Preferred certifications include Microsoft Azure AI Engineer Associate, AWS Machine Learning Specialty, and Certified Secure Software Lifecycle Professional (CSSLP).
- Ability to lead small teams, guide junior engineers, communicate effectively with clients, solve complex problems, and deliver in fast-paced consulting environments.
Benefits
- Opportunity to work on advanced AI engineering and optimization use cases.
- Exposure to global clients and large-scale enterprise AI transformations.
- Continuous learning through innovation programs, certifications, and hands-on delivery.
- Collaborative environment focused on engineering excellence and professional growth.
Tech Stack
Categories
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.