Engagement Type: Full-Time / Contractor
About CodeRoadCodeRoad is a technology execution partner trusted by companies across North America since 2002. We work alongside our clients to engineer, modernize, and scale the technology that powers their businesses, combining deep technical expertise, specialized teams, and shared accountability for outcomes. Our capabilities span product engineering, platform engineering, legacy modernization, and AI engineering.
Our engineers, designers, delivery leaders, and technology specialists collaborate through Velocity Studios: specialized teams developed within CodeRoad to deliver complex technology initiatives. Being assigned to a project means you become part of a collaborative environment where you can strengthen your expertise, take ownership of meaningful work, and grow alongside experienced professionals.
Why Build Your Career at CodeRoad?High-Velocity Work & Client Exposure: We work close to the technology, teams and roadmaps that move real outcomes. Direct engagement with U.S. client teams and roadmaps.
Career Continuity & Long-Term Opportunity: Your career here can outlast any single project. Continuous multi-project pipeline; long-tenure CodeRoaders.
Engineering Autonomy & Technical Mastery: We invest in the skills that shape what's next. Agentic AI tools and training, Coursera Enterprise, Studio practice labs, L1-L7 Career Framework.
High-Trust Employee Experience: You grow in an environment built on trust, transparency and recognition. High-touch onboarding, transparent leadership communication, community recognition, psychological safety.
Deploy & Orchestrate Agentic Pipelines: Design, deploy, and manage scalable, production-grade deployment pipelines for autonomous AI models and multi-agent workflows (LangGraph, CrewAI, n8n).
Manage Multi-Cloud AI Infrastructure: Build and maintain resilient cloud environments on GCP (Vertex AI, Cloud Functions, BigQuery) or AWS (Amazon SageMaker, AWS Lambda, S3).
Automate CI/CD & Continuous Training: Establish automated pipelines for Continuous Integration, Continuous Deployment (CI/CD), and Continuous Training (CT) using Git, Docker, and Kubernetes.
Monitor & Optimize Performance: Implement specialized observability frameworks (Langtrace, AgentOps, Prometheus, CloudWatch, Grafana) to track model drift, latency, and autonomous decision accuracy in real time.
Enforce Security & Guardrails: Implement robust security architectures including IAM, data encryption, prompt injection defense, and automated safety guardrails for compliance (GDPR).
Drive Data & Model Governance: Collaborate with cross-functional AI teams to establish data quality standards, version control, and ethical AI safeguards across the operational lifecycle.
Core Experience: 4+ years of professional experience in MLOps or DevOps, with 1+ year dedicated to deploying, evaluating, and managing production AI/ML models and agentic workflows.
Cloud Mastery: Deep hands-on experience with GCP (Vertex AI, Cloud Storage, BigQuery, Cloud Functions) or AWS (SageMaker, S3, Redshift, Lambda).
Technical & Containerization Stack: Proficiency in Python, Bash, Terraform, Docker, Kubernetes, and AI/ML orchestration tools (PyTorch, LangGraph, CrewAI, n8n).
Observability & Analytics: Hands-on expertise monitoring LLM execution, tracking data drift, and maintaining system health using tools like Langtrace, AgentOps, Prometheus, or CloudWatch.
Security & Ethical AI Mindset: Solid understanding of cloud security protocols (IAM, data privacy) and ethical AI principles (bias detection, explainability, compliance).
Language Proficiency: Advanced English skills (both written and spoken) are mandatory for seamless real-time collaboration with U.S.-based teams across East/West Coast time zones.
USA Contractor / 100% Remote
Competitive Pay (USD)
Holidays Off & Paid Time Off
Health insurance assistance program
Opportunity to work with high-growth US-based companies and cutting-edge tech stacks.
Explore opportunities and submit your application today!
Skills Required
- 4+ years of experience in MLOps, DevOps, or a related field
- At least 1 year deploying and managing AI/ML models in production
- Hands-on experience with Google Cloud Platform or Amazon Web Services
- Experience with relevant cloud services such as Vertex AI, Cloud Functions, Cloud Storage, BigQuery, SageMaker, S3, Redshift, or Lambda
- Knowledge of MLOps tools and frameworks including PyTorch, LangGraph, CrewAI, and n8n
- Proficiency with Docker and Kubernetes
- Expertise in Python and familiarity with Bash or Terraform
- Strong experience with Git and version control systems
- Experience with monitoring tools such as Lantrace, AgentOps, Prometheus, CloudWatch, or Grafana
- Experience tracking model performance, data drift, and production system health
- Understanding of cloud and MLOps security, IAM, encryption, and secure pipeline design
- Understanding of ethical AI, bias detection, explainability, and regulatory compliance such as GDPR
- Strong interpersonal, communication, and cross-functional collaboration skills
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
- Experience with agentic or autonomous AI systems
- Advanced degree or certifications in MLOps, AI/ML, or cloud technologies
What We Do
CodeRoad is a nearshore software development and technology-execution partner that helps organizations modernize applications, migrate to the cloud, build digital products, and implement enterprise AI. Its services span the full software development lifecycle, including dedicated engineering teams, platform engineering, data and AI infrastructure, legacy modernization, cloud architecture, quality automation, and DevOps. The company serves startups, enterprises, and private-equity portfolio businesses.
