Job Description:

Lead AI Engineer

Role Summary

We are seeking a technical Lead AI Engineer to lead the design, development, and implementation of cutting-edge generative AI solutions. This lead role is a unique blend of high-level architectural strategy and hands-on engineering. You will be the driving force behind our generative AI initiatives, shaping the future of our products and services by harnessing the power of Large Language Models (LLMs) and other generative technologies.

Responsibilities

• Architectural Leadership: Design and architect end-to-end generative AI solutions, from proof-of-concept to production, ensuring scalability, performance, and reliability.
• Technical Strategy: Develop and maintain a comprehensive strategic roadmap for generative AI adoption, evaluating new models, techniques, and platforms to keep our capabilities at the forefront of the industry.
• Solution Development: Lead the hands-on development of complex AI systems, including Retrieval-Augmented Generation (RAG) pipelines, autonomous AI agents, fine-tuning workflows, and custom model integrations.
• Best Practices & Standards: Establish and govern best practices for the full AI development lifecycle, including prompt engineering, model evaluation, MLOps, and data management.
• Cross-Functional Partnership: Collaborate closely with multiple management teams and business units to identify high-impact use cases and ensure the successful integration of AI solutions to meet business goals.
• Mentorship & Guidance: Serve as a senior advisor and coach to other engineers and analysts, fostering a culture of innovation and technical excellence. Allocate work and provide technical direction to the team.
• Risk & Compliance: Appropriately assess risk when business decisions are made, demonstrating consideration for the firm's reputation and safeguarding its clients and assets. Drive compliance with all applicable laws, rules, and regulations, particularly those related to AI ethics, data privacy, and model bias.
• Innovation and Research: Stay abreast of the latest advancements in generative AI research, and translate state-of-the-art developments into practical, innovative solutions.

Qualifications

• Experience: Extensive experience in designing and building AI/ML solutions, with a significant focus on generative AI and Large Language Models (LLMs).
• Gen AI Expertise: Deep understanding of modern AI architectures and techniques, including Retrieval-Augmented Generation (RAG), fine-tuning, function calling, and AI agentic workflows.
• Programming Proficiency: Expert-level skills in Python and extensive experience with core AI/ML libraries such as Py Torch, Tensor Flow.
• System Design: Proven ability to architect and develop large-scale, distributed, multi-tier applications. Strong knowledge of microservices, API design, and system integration.
• MLOps: Solid understanding of MLOps principles and experience with tools for model versioning, deployment, monitoring, and lifecycle management.
• Leadership: Demonstrated experience serving as a technical lead, architect, or principal engineer, with a track record of mentoring team members and driving projects to completion.

Good to Have Skills

• Vector Databases: Experience with vector databases and search technologies (e.g., Pinecone, Milvus, ChromaDB, Elasticsearch).
• Data Engineering: Familiarity with data pipeline development (ETL/ELT) and big data frameworks like Apache Spark or Kafka.
• Containerization: Experience with containerization and orchestration technologies such as Docker and Kubernetes for deploying and scaling AI services.
• Performance Optimization: Knowledge of distributed caching solutions (e.g., Redis, Hazelcast) and building highly performant, low-latency systems.

Job Family Group:

Technology

Job Family:

Applications Development

Time Type:

Full time

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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