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Copilot Studio / Power Platform Engineer/Architect

Design, secure, and optimize enterprise-grade Copilot Studio and Power Platform solutions that extend Microsoft 365 and Dynamics 365. You will own the full technical delivery lifecycle - from data modeling and plugin development through deployment automation and analytics - creating scalable, production-ready conversational and automation experiences.

Technical requirements

* Copilot Studio experience is an essential requirement for this role: solution authoring, generative topic orchestration, conversation boosters, custom actions, multilingual intent models, memory management, and analytics
* Integration design across Dataverse, SharePoint, Azure SQL, Cosmos DB, and external systems using custom and certified connectors with secure, role-based access
* Configuration of Azure OpenAI or Azure AI Studio endpoints to ground Copilot responses in proprietary data via retrieval-augmented generation
* Development of Power FX formulas, reusable components, and PCF controls to extend Copilot-enabled Power Apps (Canvas, Model-driven) and Power Pages portals
* Automation engineering with Power Automate cloud flows, adaptive cards, approvals, trigger conditions, and API management
* Embedding Copilot experiences into Dynamics 365, Microsoft Teams, Viva, SharePoint, web portals, and mobile apps with single sign-on and contextual data sharing
* Live demos and presales enablement: design and deliver engaging demonstrations and technical workshops that showcase solutions, accelerate stakeholder buy-in, and drive platform adoption
* Implementation of environment governance: DLP policies, solution segmentation, managed-solution ALM, conditional access, audit logging, and tenant-level analytics
* CI/CD pipelines using Azure DevOps or GitHub Actions to automate builds, tests, and releases across multiple environments
* Security architecture covering Entra ID authentication, OAuth 2.0 token handling, data masking, information protection labels, and endpoint hardening
* Monitoring and optimization with Copilot Studio analytics, Application Insights, and Power BI to measure utilization, quality, and performance while driving continuous improvement

A leading US technology company is building a new event-driven platform powered by serverless AWS services and applied AI. The team operates in a fast-paced, start-up style environment and is expanding its engineering group to accelerate green-field product development.

As a Senior Back-End Engineer you will design, implement and operate Node.js workloads running in AWS Lambda behind API Gateway. You will modernize legacy endpoints, create new APIs, and embed AI capabilities such as LLM-driven features into production systems. Daily work includes writing infrastructure as code, optimizing cold-start performance, managing data in DynamoDB and PostgreSQL, and owning the full service lifecycle from code to monitoring. You will collaborate with a hands-on technical leadership team and influence architecture choices across multiple agile pods.

Technical requirements

* Deep competence with Node.js for back-end development.
* Production experience deploying and operating AWS Lambda functions and Amazon API Gateway integrations.
* Proficiency with serverless design patterns, event buses, and infrastructure-as-code tools such as AWS SAM, CDK, or Terraform.
* Knowledge of data stores suitable for serverless workloads, especially DynamoDB and PostgreSQL.
* Hands-on work integrating AI or machine-learning services into live applications and a strong interest in advancing those capabilities.
* Ability to optimize performance, security, observability, and cost in a serverless environment.

This role focuses on building scalable data pipelines, integrating diverse data sources, and enabling predictive analytics across cloud environments.



Key Technical Requirements:

* Strong hands-on experience developing data pipelines using Python
* Strong SQL skills, including performance tuning, stored procedures, and data modeling (Star/Snowflake schemas)
* Proven experience with Azure Data Factory (ADF) and Azure Synapse
* Experience with ETL orchestration tools such as Apache Airflow
* Skilled in working with structured and unstructured data, including ingestion from APIs (REST/JSON/XML)
* Familiarity with cloud-based warehousing tools such as Snowflake, Redshift, or BigQuery
* Comfortable working in Azure and/or hybrid cloud environments (Azure/AWS)
* Experience supporting machine learning or predictive modeling pipelines
* Familiar with containerization and version control: Docker, Git, and Azure DevOps
* Understanding of data serialization formats (Parquet, Avro, JSON)
* Knowledge of data validation, quality checks, and observability tools (Azure Monitor, logging frameworks, etc.)



Candidates will be expected, during the interview process, to demonstrate deep hands-on technical experience in data pipeline development, cloud orchestration, and ML-ready data infrastructure.



This position will require the successful applicant to work 5 days per week on site.

This role focuses on building scalable data pipelines, integrating diverse data sources, and enabling predictive analytics across cloud environments.



Key Technical Requirements:

* Strong hands-on experience developing data pipelines using Python
* Strong SQL skills, including performance tuning, stored procedures, and data modeling (Star/Snowflake schemas)
* Proven experience with Azure Data Factory (ADF) and Azure Synapse
* Experience with ETL orchestration tools such as Apache Airflow
* Skilled in working with structured and unstructured data, including ingestion from APIs (REST/JSON/XML)
* Familiarity with cloud-based warehousing tools such as Snowflake, Redshift, or BigQuery
* Comfortable working in Azure and/or hybrid cloud environments (Azure/AWS)
* Experience supporting machine learning or predictive modeling pipelines
* Familiar with containerization and version control: Docker, Git, and Azure DevOps
* Understanding of data serialization formats (Parquet, Avro, JSON)
* Knowledge of data validation, quality checks, and observability tools (Azure Monitor, logging frameworks, etc.)



Candidates will be expected, during the interview process, to demonstrate deep hands-on technical experience in data pipeline development, cloud orchestration, and ML-ready data infrastructure.



This position will require the successful applicant to work 5 days per week on site.