Mid-Level Full-Stack Engineer - .NET, Azure & AI
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Summary
Fully remote, hands-on mid-level full-stack engineer at Chiri who joins forward-deployed client engagements: modernizing existing .NET apps and building new AI-native products. Core stack is C#/.NET (ASP.NET Core), React/TypeScript, Microsoft Azure, Terraform IaC, CI/CD, and LLM/agentic AI integrations with production-grade security.
Why Chiri
The convergence of human and digital workforces is changing how companies build, operate, and scale.
Chiri works directly with organizations to turn that shift into working systems. Our forward-deployed teams operate inside the technologies and processes our clients already use, combining modern software engineering, AI, and practical operating expertise to build capabilities that work in the real world.
We are looking for ambitious builders who want to help shape what comes next.
Role Overview
Chiri is looking for a hands-on Mid-Level Full-Stack Engineer to work on forward-deployed client engagements spanning existing platform modernization and the development of new AI-native applications.
This is not a narrowly defined development role. You may step into an established .NET application that needs to be secured, modernized, tested, and prepared to scale, or work with a client to build new product capabilities around AI.
You will work directly with client engineering, product, and leadership teams. We are looking for someone who can understand an existing environment quickly, work within established architectural guardrails, make sound technical decisions, and personally carry those decisions through implementation.
This is a hands-on engineering role. We are looking for someone with roughly 3 - 4+ years of professional experience who is comfortable working independently, navigating unfamiliar codebases, and taking ownership of getting things done.
Key Responsibilities
- Build and extend production applications using C#, .NET / ASP.NET Core, modern JavaScript/TypeScript, and React.
- Work across existing brownfield applications and new product development rather than assuming everything should be rewritten.
- Design and build AI-native application capabilities, including LLM integrations, agentic workflows, tool use, structured outputs, retrieval, grounding, human-in-the-loop workflows, and AI evaluation.
- Integrate AI components into traditional application architectures with appropriate security, reliability, observability, and deterministic controls.
- Design, build, and operate production environments in Microsoft Azure.
- Work with Azure services including App Service, Azure SQL, Storage, Key Vault, networking, managed identities, monitoring, backup, and security services.
- Define and manage cloud infrastructure using Terraform and infrastructure as code, including existing production environments where appropriate.
- Build automated CI/CD pipelines covering compilation, automated testing, security scanning, infrastructure changes, and deployment.
- Establish and improve automated testing across application, API, and front-end layers.
- Design and improve APIs, authentication, authorization, role-based access, secrets management, and application security.
- Work with relational data across SQL Server, Azure SQL, PostgreSQL, Supabase, and related platforms.
- Build data ingestion and transformation workflows for structured and semi-structured information.
- Design administrative and operational interfaces that allow non-technical users to manage data, users, workflows, and application behavior without developer intervention.
- Work closely with product and design stakeholders to turn customer needs into practical application experiences.
- Diagnose unfamiliar systems, identify technical risk, and create order in environments that have accumulated years of development decisions.
- Document systems, architectural decisions, operating procedures, and technical tradeoffs so clients can operate what we build.
Required Skills and Experience
You are an engineer who can own an outcome rather than simply execute predefined tickets.
You should bring:
- Strong production experience with C#, .NET / ASP.NET Core, REST APIs, and modern application architecture.
- Strong full-stack development skills, including React and TypeScript/JavaScript.
- Deep hands-on experience with Microsoft Azure and operating real production applications in the cloud.
- Experience with Terraform or comparable infrastructure-as-code tooling.
- Strong experience building and maintaining CI/CD pipelines, automated tests, Git-based workflows, and production release processes.
- Strong SQL and relational data-modeling fundamentals.
- Experience integrating external APIs and services into production applications.
- Solid application-security fundamentals, including authentication, authorization, secret management, encryption, dependency management, least-privilege access, and secure handling of sensitive data.
- Experience using modern AI models and APIs as part of production software, not simply as developer productivity tools.
- Understanding of the engineering challenges created by probabilistic AI systems, including testing, evaluation, grounding, observability, and guardrails.
- The architectural judgment to determine when AI should be used and when conventional application logic is the better solution.
- The ability to take partially defined requirements, ask the right questions, make sensible technical decisions, and move the work forward.
- Clear written and verbal English and the ability to communicate effectively with engineers, executives, product teams, and non-technical stakeholders.
Preferred Qualifications
- Experience modernizing or taking ownership of an established brownfield .NET application.
- Experience building AI-native SaaS products or agentic applications.
- Experience with Supabase and PostgreSQL, particularly as part of a larger cloud architecture.
- Experience with Azure private networking, Private Endpoints, Azure Policy, Defender for Cloud, managed identities, and production security hardening.
- Experience with GitHub-based CI/CD and repository administration.
- Healthcare technology experience or experience working with PHI, HIPAA-regulated data, or similarly sensitive information.
- Experience with data anonymization, de-identification, tenant isolation, audit logging, and secure data architecture.
- ETL, spreadsheet ingestion, catalog, assessment, or other data-intensive application workflows.
- Product-minded engineering experience with a strong understanding of customer experience and usability.
- Consulting, client-facing engineering, or forward-deployed engineering experience.
- Experience working alongside a CTO, chief architect, or client technical leadership while retaining hands-on ownership of implementation.
How You Work
You are pragmatic. You know when to repair something, when to replace it, and when the smartest engineering decision is to leave it alone.
You are equally comfortable opening an unfamiliar five-year-old codebase and figuring out why production behaves the way it does or sitting with a client at the beginning of a new product and helping turn an architectural direction into working software.
You think beyond code. Security, deployment, testing, observability, data integrity, recoverability, usability, and maintainability are all part of the product.
You understand that AI changes how software can be built, but not the responsibility that comes with shipping it. You use modern AI development tools aggressively and know how to design applications around models and agents, but you test, verify, secure, and own what goes into production.
You do not need every detail prescribed before you begin. Give you the business objective, the existing environment, and the architectural guardrails, and you can help determine the path from there.
Most importantly, you take ownership. You leave systems more understandable, more secure, more scalable, and easier for the people who inherit them to operate.
What We Offer
- A fast-paced, fully remote environment with meaningful ownership.
- The opportunity to help define what “enterprise-ready AI” actually means.
- Access to cutting-edge AI tools, models, and internal playbooks.
- The chance to help clients achieve tangible outcomes - like 50% faster workflows - without compromising governance or trust.
- Direct collaboration with experienced engineers and company leadership.
- The opportunity to grow from feature ownership into broader technical and architectural responsibility.
- A culture that values curiosity, continuous learning, and pragmatic problem-solving.