AI/ML Engineer

Accountabilities:
The AI/ML Engineer is responsible for designing, developing, and maintaining the data pipelines, AI models, and intelligent applications that support business-critical products. This role combines data engineering expertise with machine learning development, requiring strong technical execution, attention to quality, and a commitment to building secure and scalable solutions. Build and maintain reliable data ingestion pipelines using Python, cloud data platforms, and modern ELT technologies, including API, PostgreSQL, and change-data-capture integrations. Develop scalable data transformations and trusted datasets that support analytics, reporting, machine learning workflows, and AI-powered applications. Implement data-quality frameworks, monitoring, documentation, lineage tracking, and validation processes to ensure accuracy and reliability. Design and optimize machine learning workflows, including model evaluation, prompt engineering, regression testing, and output validation. Develop and integrate large language model solutions, AI agents, and intelligent workflows using platforms such as AWS Bedrock and modern AI frameworks. Collaborate with product and engineering teams to deliver AI-powered features from concept through production deployment. Build production-quality software with strong testing practices, documentation, error handling, and maintainability. Implement AI safety measures, including guardrails, monitoring, traceability, and controls for sensitive information. Support secure processing of sensitive data by ensuring appropriate masking, access controls, retention policies, and compliance requirements. Monitor and improve system performance, including data processing efficiency, model reliability, latency, and infrastructure costs. Optimize cloud resources, data warehouse performance, model usage, and AI workflows to improve scalability and cost efficiency. Create operational processes, recovery procedures, and documentation to support reliable AI and data systems. Requirements: The ideal candidate is a technically skilled engineer with experience building data-driven applications, machine learning solutions, and scalable software systems. They combine strong programming skills with curiosity, problem-solving ability, and a passion for emerging AI technologies. Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related technical field. 2+ years of experience in data engineering, software engineering, machine learning engineering, or a related discipline. Advanced proficiency in Python and SQL. Hands-on experience integrating large language models through platforms such as AWS Bedrock, Anthropic Claude, OpenAI API, or similar technologies. Experience with dbt or comparable data transformation and testing frameworks. Experience working with Snowflake or similar cloud data warehouse technologies. Experience with AWS Lambda, serverless architectures, or comparable cloud development environments. Familiarity with data ingestion tools such as Fivetran, workflow orchestration tools such as Airflow, and AI frameworks such as LangChain or CrewAI is preferred. Knowledge of vector databases, cloud infrastructure, deployment automation, and modern application architectures is a plus. Familiarity with machine learning evaluation methods, prompt engineering techniques, and AI safety practices. Strong understanding of software development best practices, testing methodologies, and production reliability. Ability to work independently, prioritize multiple initiatives, and operate effectively in a distributed environment. Strong communication, collaboration, and problem-solving skills with a high level of accountability and initiative. Professional integrity, ethical judgment, and commitment to protecting sensitive information. Fluent English communication skills and authorization to work in the United States. Benefits: Competitive compensation package. Remote work flexibility. Opportunity to work on advanced AI, machine learning, and data engineering initiatives. Collaborative environment focused on innovation and meaningful technology solutions. Access to modern cloud, AI, and engineering tools. Professional growth opportunities in an expanding technology organization. Supportive team culture that values creativity, ownership, and collaboration.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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