Ai Engineer Jobs

About The Position

Requirements

• At least 5 years of relevant consulting or industry experience in a hands-on development role, working across borders and as an integral team member.
• At least 5 years of full-stack software development experience, including proficiency in at least one back-end language (Python, Java, .NET/C#, Go, or Node.js) and a modern front-end framework.
• At least 4 years of experience building microservices and scalable APIs in a distributed enterprise environment.
• Knowledge of relational and/or NoSQL databases such as PostgreSQL, MySQL, MongoDB, or DynamoDB.
• Experience with AWS, GCP, or Azure and containerized environments such as Docker and Kubernetes.
• Strong problem-solving skills and ability to debug and optimize complex systems.
• A track record of managing or technically leading delivery teams, including communication cadences and quality assurance across time zones.
• Experience delivering software using multiple SDLC methodologies, such as Agile, SAFe, Kanban, or waterfall-agile hybrid.
• Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience.
• Ability to travel up to 50%, based on the work, clients, and industries or sectors served.
• Ability to work independently and collaboratively, communicate effectively, maintain attention to detail and quality, build professional relationships, lead projects or workstreams, prioritize multiple tasks, meet deadlines, and provide clear guidance.

Nice To Haves

• Experience with event-driven architectures and messaging systems such as Kafka, RabbitMQ, or SQS.
• Contributions to open-source projects or a demonstrated personal portfolio.
• Experience with machine learning pipelines or data engineering workflows.
• Professional experience designing and delivering solutions incorporating large language models (LLMs) and/or agentic AI architectures.
• Knowledge of security best practices, including OWASP guidelines and secure coding standards.
• Prior experience as a tech lead or staff engineer.
• Industry-recognized technology certifications.

Responsibilities

• Architect, design, and implement scalable, reliable, and maintainable full-stack software systems and services.
• Design and operationalize RESTful and asynchronous APIs on cloud-native infrastructure, including containerized workloads, CI/CD pipelines, and infrastructure-as-code.
• Lead end-to-end delivery of complex features, from requirements gathering through deployment and monitoring.
• Architect and deliver production-grade agentic AI and multi-agent applications, including orchestrator-agent hierarchies, RAG pipelines, tool-calling agents, and context and memory management.
• Conduct code reviews, enforce coding standards, and promote engineering best practices.
• Mentor and guide junior and mid-level engineers and encourage continuous learning and improvement.
• Collaborate with Product, Design, DevOps, and QA teams to deliver high-quality software.
• Identify technical debt and drive refactoring and improvement initiatives.
• Participate in system design discussions, architecture reviews, and technical planning sessions.
• Troubleshoot and resolve complex performance, scalability, and reliability issues in production systems.
• Contribute to hiring through technical interviews and assessments.

Benefits

• Employees are offered a broad range of benefits; specific benefits are not listed.
• Potential eligibility for a discretionary annual incentive program, subject to program rules and individual and organizational performance.
• Opportunities for professional development, including on-the-job learning, formal development programs, leadership opportunities, and mentorship.