Summary
Role 1: ( 1K Agents )
We are looking for an experienced contractor who is highly proficient in Python and has practical experience developing AI-powered systems. The preferred candidate should have worked with AI agents, Model Context Protocol (MCP), modern data management techniques, and cloud platforms to create scalable, production-ready solutions.
Core Responsibilities
- Design, build, and maintain Python based services and automation workflows
- Implement MCP for agent communication, control, and observability
- Build, transform, and manage data pipelines supporting AI and analytics use cases
- Deploy, monitor, and optimize solutions in cloud environments
- Collaborate with product, data, and engineering teams to deliver end-to-end solutions
- Ensure code quality, performance, security, and maintainability
Required Technical Skills
- Python: Advanced proficiency; production experience with APIs, async processing, and testing
- AI / LLM Agents: Experience designing and implementing autonomous or semiautonomous AI agents (e.g., tool using agents, planners, orchestrators)
- MCP (Model Context Protocols): Experience with agent communication, coordination frameworks, or protocol driven AI architectures
- Data Management:
- Data modeling and data pipelines
- Working with SQL and NoSQL databases
- Experience with data quality, governance, and large‐scale datasets
- Cloud Experience:
- Hands on work in at least one major cloud platform (Azure, AWS, or GCP)
- Experience with cloud storage, compute, and managed services
- Familiarity with CI/CD and cloud native deployment patterns
Preferred / Nice to Have
- Experience with vector databases and embeddings
- Familiarity with MLOps or LLMOps practices
- Experience with streaming data or event driven architectures
- Knowledge of security and compliance considerations for AI systems
- Prior work in enterprise or large-scale data management
- Healthcare or other data regulated experience preferred
Engagement Characteristics
- Contractor is expected to work independently with minimal supervision
- Comfortable operating in fast moving, evolving technical environments
- Strong documentation and communication skills
- Experience collaborating with remote and cross functional teams
Technical Skills
- AI/LLM Agent and MCP (Model Control Protocols) - Google ADK, Copilot Studio
- Cloud Experience - Google Cloud or Azure preferred.
- Database Knowledge - BigQuery, Firestore, Cloud SQL, etc.
- Data pipeline - Dataflow
- Power Automate
- Automation Tooling - UI Path, etc.
- CI/CD Pipeline - Azure DevOps Pipeline
- Infrastructure as Code (IaC) - Terraform
Role 2:
Job Title: Infrastructure Engineer (Terraform, CI/CD, GCP & Azure, Data & AI Platforms)
About The Role
We are looking for an experienced
Infrastructure Engineer to design, automate, and operate scalable cloud infrastructure supporting
data platforms and AI/ML workloads across
GCP and Azure. This role focuses on
Infrastructure such as Code,
CI/CD automation,
cloud networking, and enabling reliable, secure environments for data engineering and analytics teams.
Key Responsibilities
- Design, provision, and manage cloud infrastructure using Terraform
- Build and maintain CI/CD pipelines using Azure DevOps
- Provision and manage GCP infrastructure, including compute, storage, IAM, and networking
- Support and manage Azure infrastructure (VNets, networking, compute, storage)
- Design and implement network provisioning (VPC/VNet architecture, routing, firewalls, load balancers, private connectivity)
- Build and operate infrastructure for data platforms (data lakes, warehouses, streaming, analytics platforms)
- Provision and support AI/ML infrastructure, including GPU resources and AI platforms
- Implement security best practices, IAM, encryption, and compliance controls
- Optimize infrastructure for performance, reliability, and cost
- Collaborate with data engineering, analytics, and ML teams
- Document infrastructure, architecture, standards, and operational runbooks
Required Skills & Qualifications
- Strong experience with Terraform (Infrastructure as Code)
- Experience with CI/CD pipelines, preferably Azure DevOps
- Strong hands-on experience with Google Cloud Platform (GCP)
- Solid understanding of cloud networking and network provisioning
- Experience supporting data platforms or large-scale data workloads
- Experience with AI/ML infrastructure
- Strong Linux and scripting skills (Bash, Python, etc.)
Preferred / Nice To Have
- Hands-on experience with Azure infrastructure
- Experience with Kubernetes (GKE / AKS)
- Experience with data services such as BigQuery, Dataflow, Dataproc, Synapse, ADLS, Snowflake
- Monitoring and observability tools (Prometheus, Grafana, Cloud Monitoring)
- Multi-cloud experience and relevant certifications
