Sr SW engineer- AIML

As a Staff AI Engineer youll lead enterprise full stack and AI platform architecture at scale for multiple initiatives across the company. Youll design and ship microservices and REST APIs build RAG and multimodal LLM features and set standards for AI-assisted development. Youll make technical decisions end-to-end balancing reliability performance and cloud cost for AI systems.
You will partner with globally distributed teams to engage intervene and accelerate assimilation of AI into Grid SW services activities that drive tangible outcomes

Key Responsibilities:

• Identify and deliver reusable AI components for forward-deployed engineers.
• Ship resilient REST APIs and microservices.
• Build RAG and multimodal LLM features.
• Design agentic workflows for autonomous tasks.
• Mentor engineers and provide guidance to contractors and partners.

Required Qualifications:

• Bachelors degree in computer science Computer Engineering or a related technical field.
• 10 years of experience with at least one general purpose programming language (Python preferred Java or Go) and front-end experience with JavaScript/TypeScript.
• Proven track record shipping production applications that incorporate LLMs or AI services at scale.
• Demonstrated experience leading technical teams and providing guidance to external contractors or vendors.
• Demonstrated experience of driving at least 5 projects with strong AI & ML engagement
• Strong experience with cloud platforms (AWS GCP or Azure) and advanced containerization (Docker Kubernetes).
• Experience with technical oversight code review processes and quality assurance methodologies.
• Strong trouble shooting skills
• Good communication skills and prior experience of working with globally distributed teams

Preferred Qualifications:

• Experience in AI/ML including architectural design technical leadership and system optimization.
• Having a masters degree or equivalent in AI is a plus.
• Experience with modern integration frameworks (SOAP Rest MuleSoft ) and advanced state management.
• Experience with vector databases (e.g. Milvus Pinecone Weaviate pgvector) and embedding model optimization.
• Experience with multiple LLM providers and advanced AI-orchestration frameworks (e.g. LangChain LlamaIndex).
• Experience with enterprise RAG architectures semantic search optimization and conversation memory management at scale.
• Experience building and scaling AI-powered features for 100k users.