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

TALENT Software Services

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