About this role
The Gen AI - Engineering Lead will drive the design, development, and deployment of enterprise-grade Generative AI solutions. This role involves leading the end-to-end lifecycle of GenAI initiatives, from translating business requirements into prototypes to delivering scalable, production-ready applications. Responsibilities include architecting AI workflows, establishing prompt governance, implementing model guardrails, and optimizing performance across AWS, GCP, and Snowflake ecosystems. Key duties include:
Solution Design & Orchestration: Architect enterprise-scale GenAI solutions using LLMs and agentic frameworks. Build scalable orchestration pipelines using tools like LangGraph, LangChain, or CrewAI.
Governance & Evaluation: Develop prompt engineering frameworks, versioning, and lifecycle management. Establish AI guardrails to mitigate hallucinations and bias. Define benchmarking methodologies for accuracy, latency, and safety.
Cloud & Data Engineering: Design RAG architectures incorporating vector databases and semantic search. Leverage cloud-native services such as Amazon Bedrock, SageMaker, Vertex AI, and Snowflake Cortex AI.
Qualifications
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
- Minimum 6 years of experience in software engineering, ML, or AI development (as per the 6-9 years range).
- 4+ years of hands-on experience with Generative AI and LLMs.
- Strong proficiency in Python and modern AI/ML frameworks.
- Proven ability to translate business requirements into production-ready AI solutions.