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Position: AI Engineering Team Lead
Location: Stamford CT - Onsite / Hybrid / Remote
Duration: 6 months
Job Summary:
About the Role The AI Engineering Team Lead will be responsible for driving AI-based solution development to support United Rentals' strategic initiatives. This role will focus on designing and delivering intelligent, scalable, and secure AI solutions by leveraging cutting-edge technologies such as Amazon Bedrock, SageMaker, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering.
The position requires a deep understanding of cloud-native architectures, machine learning operations, and modern data pipelines. The successful candidate will partner with business and technology teams to design and implement AI systems that integrate seamlessly across SQL and NoSQL databases, vectorization pipelines, and AWS cloud infrastructure.
Key Responsibilities:
Architect, design, and implement AI-based solutions leveraging AWS services (Amazon Bedrock, SageMaker, Lambda, ECS, S3, etc.) and advanced machine learning techniques.
Build and manage data vectorization pipelines to support RAG and LLM-based applications.
Define and implement scalable AI architectures that integrate with enterprise data platforms, SQL, and NoSQL systems.
Drive best practices in AI/ML model deployment, monitoring, and lifecycle management (MLOps).
Collaborate with cross-functional teams to align AI solutions with business goals and technical standards.
Provide technical leadership in areas of prompt engineering, generative AI, AI agents, AI tools and knowledge retrieval systems.
Direct, develop and mentor staff:
Provide direction to staff to increase their ability to positively impact the business and achieve desired results.
Initiate career development and training plans to ensure succession of IT leaders.
Establish goals and assess performance in a timely manner.
Foster an atmosphere and environment of collaboration, teamwork and open communication
Evaluate emerging AI technologies and recommend adoption strategies.
Ensure compliance, scalability, and security across AI solution deployments.
Provide input to IT strategic plan and architecture
Provide thought leadership in the select of new technologies to support business needs and deprecate legacy technologies
Continuously improve and modernize the existing architecture consisting of on premise and cloud
Ensure applications are designed and developed in a secure and extensible architecture
Qualifications:
Bachelor's or Master's degree in Computer Science, Data Science, or related field.
15 years of experience in software engineering/architecture, with at least 3 5 years in AI/ML solution design.
Proven expertise in AWS cloud services (Bedrock, SageMaker, Lambda, API Gateway, etc.).
Strong knowledge of LLMs, RAG pipelines, embeddings, and vector databases (e.g., Pinecone, FAISS, or similar).
Experience with modern data architectures, ETL/ELT pipelines, and integrating SQL & NoSQL databases.
Hands-on experience with MLOps frameworks and tools.
Proficiency in Python, and familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Hugging Face.
Excellent problem-solving, communication, and leadership skills
Position: AI Engineering Team Lead
Location: Stamford CT - Onsite / Hybrid / Remote
Duration: 6 months
Job Summary:
About the Role The AI Engineering Team Lead will be responsible for driving AI-based solution development to support United Rentals' strategic initiatives. This role will focus on designing and delivering intelligent, scalable, and secure AI solutions by leveraging cutting-edge technologies such as Amazon Bedrock, SageMaker, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering.
The position requires a deep understanding of cloud-native architectures, machine learning operations, and modern data pipelines. The successful candidate will partner with business and technology teams to design and implement AI systems that integrate seamlessly across SQL and NoSQL databases, vectorization pipelines, and AWS cloud infrastructure.
Key Responsibilities:
Architect, design, and implement AI-based solutions leveraging AWS services (Amazon Bedrock, SageMaker, Lambda, ECS, S3, etc.) and advanced machine learning techniques.
Build and manage data vectorization pipelines to support RAG and LLM-based applications.
Define and implement scalable AI architectures that integrate with enterprise data platforms, SQL, and NoSQL systems.
Drive best practices in AI/ML model deployment, monitoring, and lifecycle management (MLOps).
Collaborate with cross-functional teams to align AI solutions with business goals and technical standards.
Provide technical leadership in areas of prompt engineering, generative AI, AI agents, AI tools and knowledge retrieval systems.
Direct, develop and mentor staff:
Provide direction to staff to increase their ability to positively impact the business and achieve desired results.
Initiate career development and training plans to ensure succession of IT leaders.
Establish goals and assess performance in a timely manner.
Foster an atmosphere and environment of collaboration, teamwork and open communication
Evaluate emerging AI technologies and recommend adoption strategies.
Ensure compliance, scalability, and security across AI solution deployments.
Provide input to IT strategic plan and architecture
Provide thought leadership in the select of new technologies to support business needs and deprecate legacy technologies
Continuously improve and modernize the existing architecture consisting of on premise and cloud
Ensure applications are designed and developed in a secure and extensible architecture
Qualifications:
Bachelor's or Master's degree in Computer Science, Data Science, or related field.
15 years of experience in software engineering/architecture, with at least 3 5 years in AI/ML solution design.
Proven expertise in AWS cloud services (Bedrock, SageMaker, Lambda, API Gateway, etc.).
Strong knowledge of LLMs, RAG pipelines, embeddings, and vector databases (e.g., Pinecone, FAISS, or similar).
Experience with modern data architectures, ETL/ELT pipelines, and integrating SQL & NoSQL databases.
Hands-on experience with MLOps frameworks and tools.
Proficiency in Python, and familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Hugging Face.
Excellent problem-solving, communication, and leadership skills