Lead AI Engineer

This is a fully remote position, open to applicants in United States, +2 more countries.

📋 Description

• Design, create, and implement production-ready AI applications, copilots, retrieval systems, and agentic workflows.

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

• Develop backend services, APIs, and application architectures that integrate AI functionalities into enterprise systems.

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

• Launch AI solutions into production while ensuring security, observability, monitoring, evaluation, and governance.

• Connect AI systems with enterprise data platforms, APIs, databases, messaging systems, and business applications.

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

• Deploy and manage containerized applications on Kubernetes, focusing on scaling, service networking, resource management, and production monitoring.

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

• Keep up-to-date with emerging AI technologies and suggest practical strategies that enhance client outcomes.

⛳️ Requirements

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

• 3+ years of professional experience in software engineering with a focus on building production applications.

• 1+ years of experience in designing and deploying AI or machine learning solutions in a production environment.

• Proficient in programming languages such as Python, Java, C#, Go, TypeScript, or similar.

• Experience in developing scalable backend systems, APIs, or distributed applications.

• Background in creating AI applications using modern LLMs, machine learning models, or intelligent automation solutions.

• Knowledge of online and offline evaluation, observability, context engineering, guardrails, and AI governance.

• Familiarity with MLOps, LLMOps, or production deployment pipelines.

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

• Experience using tools like Claude Code, OpenAI Codex, Google Antigravity, Cursor, GitHub Copilot, or similar coding environments.

• Proven experience in integrating AI applications with enterprise data sources, APIs, and business systems.

• Familiarity with cloud platforms such as AWS, Azure, GCP, Databricks, Snowflake, or similar technologies.

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

• Excellent communication skills with the ability to articulate technical concepts to both technical and non-technical stakeholders.

• Capability to independently manage technical workstreams while working collaboratively across multidisciplinary teams.

• Preferred: experience with FastAPI, Flask, Spring Boot, .NET, Express, multi-agent systems, AI workflows, agents, semantic search, vector databases, knowledge graphs, distributed systems, concurrency, high-scale cloud applications, AI solutions serving over 1000 users, consulting or enterprise customers, data pipelines, or LLM pre-training/fine-tuning.

🏝️ Benefits

• Opportunity to work on cutting-edge AI technologies and applications.

• Collaborative and inclusive work environment that values diverse perspectives.

• Professional development and growth opportunities within the AI Engineering field.

• Competitive salary and comprehensive benefits package.