Opsfleet

We are a boutique cloud consulting company looking to expand our remote team of 50+ engineers.

As a services company, we focus on building long-term relationships with our clients. We don't believe in micromanagement (no time tracking here) and expect our engineers to take ownership while being proactive and creative in their work.

We specialize in DevOps and Cloud operations, primarily on AWS and Google Cloud, including expertise in GenAI/LLM-Ops supported by our AI team. Our team also has extensive Kubernetes experience, having worked with the container orchestration platform since its early development stages.

We are seeking engineers with strong communication skills to help our clients:

• Migrate from manual cloud configuration to infrastructure-as-code using Terraform/Terragrunt, CloudFormation & Crossplane
• Containerize applications and implement Docker workflows in existing build pipelines using GitHub Actions, GitLab, CircleCI, or Jenkins
• Handle day-one operations: deploy Kubernetes clusters across cloud providers and configure essential add-ons like Karpenter and ingress controllers
• Manage day-two operations: package applications with Helm, implement GitOps-based continuous deployment using ArgoCD/Flux, optimize costs using Graviton/Arm64 and Spot instances, support incident resolution, and deploy Istio for mTLS and observability.
• Enhance application observability through monitoring tools including Prometheus, Loki, Grafana, EFK, eBPF-based solutions like Pixie, and advanced services such as APM and RUM
• Strengthen application security through DevSecOps practices, leveraging cloud tools like CloudTrail, SecurityHub, GuardDuty, and integrating security scanners such as Snyk and Wiz into CI/CD pipelines
• Support AI engineers in building and managing AI/ML pipelines, integrate infrastructure and data with LLMs, and optimize GPU efficiency through scheduling optimization, GPU Time Slicing, etc.
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Being part of a team of 50+ senior DevOps engineers comes with great benefits: you'll always have someone to learn from and colleagues ready to help with technical questions or brainstorming sessions.

If you're interested and would like to learn more about the position, please reach out to us.

Talk soon!!

We are seeking a talented and experienced AI Engineer with a Data Science background to join our professional services team of 50+ engineers. The position is available full-time, with part-time arrangements possible for the right candidate. This remote-first role focuses on Generative AI development, specifically building and deploying advanced Large Language Models (LLMs) and AI agents. You'll work with state-of-the-art foundation models through platforms like AWS Bedrock and GCP Vertex AI to develop innovative GenAI applications and scalable AI infrastructure for our clients.

Key Responsibilities:

Generative AI Development:

• Design and implement production-ready generative AI applications and AI agents using foundation models and cutting-edge protocols like MCP and A2A
• Fine-tune and optimize LLMs for specific use cases and domains
• Create and maintain prompt engineering strategies and evaluation frameworks
• Design and deploy autonomous AI agents with targeted capabilities

AI/ML Engineering:

• Build end-to-end LLM pipelines for fine-tuning, deployment, and monitoring
• Implement RAG (Retrieval-Augmented Generation) systems
• Create efficient vector storage and embedding solutions

Infrastructure and Operations:

• Build and maintain robust AI infrastructure using AWS and GCP services
• Implement monitoring systems for model performance and infrastructure health
• Optimize cloud resources for cost-efficiency while maintaining performance

Preferred Qualifications:

• 4+ years of experience in AI, machine learning, or data science, with a recent focus on Generative AI
• Strong programming skills and experience with LLM and Agent frameworks (LangChain, CrewAI)
• Expertise in cloud platforms (AWS, GCP) and containerization technologies
• Deep understanding of LLM operations, including prompt engineering and RAG
• Experience with vector databases and semantic search implementations
• Experience building and deploying AI agents using modern frameworks
• Strong analytical and problem-solving abilities

Employment Options:

• Full-time position (40 hours/week)
• Part-time arrangements available for qualified candidates (minimum 20 hours/week)

Benefits:

• Potential career paths include AI Team Lead
• Collaborative remote team environment
• Opportunity to contribute to open-source GenAI initiatives and research publications