3 days ago
Coimbatore, IndiaSenior
Responsibilities
- Design and build LLM application components including prompts, tools, agents, orchestration flows, memory and context handling, retrieval pipelines, and evaluation harnesses.
- Create Foundry-based agents and integrate enterprise tools, knowledge, memory, Azure AI Search, API Management, Logic Apps, and Functions.
- Implement data ingestion, parsing, chunking, enrichment, embeddings, vector search, and retrieval workflows for structured and unstructured content.
- Engineer safety, privacy, security, governance, authentication, authorization, lineage, audit logging, guardrails, and prompt-injection defenses.
- 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.
- 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 coding experience in Python and strong understanding of APIs, distributed systems, CI/CD, testing, observability, and secure SDLC practices.
- Experience delivering AI/ML or data products in banking, insurance, healthcare, public sector, retail, energy, or another relevant industry domain.
- Experience with Microsoft Foundry or Azure AI Foundry, Foundry Agent Service, Azure OpenAI models, Azure AI Search, Prompt Flow, Azure Functions, Logic Apps, API Management, Event Grid, Microsoft Fabric, Entra ID, Key Vault, Azure Monitor, and Application Insights.
- Understanding of RAG, function and tool calling, agent orchestration, model invocation, prompt engineering, embeddings, vector databases, and evaluation metrics.
- Knowledge of traditional ML and GenAI components across data preparation, model integration, deployment, monitoring, and continuous improvement.
- Practical 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 Azure AI Engineer, Azure Solutions Architect, or Azure Developer certification experience; Microsoft Fabric, Semantic Kernel, Prompt Flow, private networking, Defender for Cloud, Responsible AI governance, and open-source AI framework experience.
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.