Senior AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Create, construct, and implement production-level AI applications, copilots, retrieval systems, and agentic workflows.

• Convert business challenges into scalable technical solutions by employing contemporary AI engineering best practices.

• Develop backend services, APIs, and application architectures that embed AI functionalities within enterprise systems.

• Construct multi-agent systems, AI agents, workflow automation, and decision-support frameworks.

• Launch AI solutions into production with the necessary security, observability, monitoring, evaluation, and governance measures.

• Design AI systems that seamlessly integrate with enterprise data platforms, APIs, databases, messaging frameworks, and business applications.

• Collaborate with multidisciplinary client teams, including engineering, data, product, architecture, security, and business stakeholders.

• Have experience in deploying and managing containerized applications on Kubernetes, encompassing scaling, service networking, resource management, and production monitoring.

• Contribute reusable accelerators, frameworks, technical assets, and thought leadership that enhance the AI Engineering practice.

• Keep abreast of emerging AI technologies and propose practical strategies to enhance client outcomes.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field with equivalent practical experience.

• Minimum of 3 years of professional software engineering experience in developing production applications.

• At least 1 year of experience in designing and deploying AI or machine learning solutions in production.

• Strong programming skills in Python, Java, C#, Go, TypeScript, or similar programming languages.

• Proven experience in building scalable backend systems, APIs, or distributed applications.

• Familiarity with developing AI applications utilizing modern LLMs, machine learning models, or intelligent automation solutions.

• Experience with online and offline evaluation, observability, context engineering, guardrails, and AI governance.

• Proficient in MLOps, LLMOps, or production deployment pipelines.

• Strong grasp of software engineering principles, including testing, version control, CI/CD, code reviews, and system design.

• Experience with tools such as Claude Code, OpenAI Codex, Google Antigravity, Cursor, GitHub Copilot, or other similar coding frameworks.

• Knowledge of integrating AI applications with enterprise data sources, APIs, and business systems.

• Familiarity with cloud platforms like AWS, Azure, GCP, Databricks, Snowflake, or comparable technologies.

• Experience in deploying applications using containers, Kubernetes, serverless platforms, or other cloud-native technologies.

• Excellent communication skills, capable of articulating technical concepts to both technical and non-technical stakeholders.

• Ability to independently manage technical workstreams while collaborating with multidisciplinary teams.

🏝️ Benefits

• Health insurance.

• Professional development opportunities.

• 401(k) matching.