AI-Assisted Development Specialist / Agentic AI Engineer / AI Architect

Employvision Inc. is recruiting for AI-Assisted Development Specialist, Agentic AI Engineer, and AI Architect positions supporting a healthcare client. The roles focus on AI-assisted software development, autonomous agent systems, and enterprise AI architecture using Microsoft Azure, while addressing healthcare security, compliance, governance, and scalability requirements.

Responsibilities:

• Use GitHub Copilot and other AI coding assistants (e.g., Cursor, Claude Code) to write, refactor, and debug code across front-end, middle-tier, and backend layers, including .NET (C#) and Python codebases
• Design and implement cloud-based solutions with an emphasis on Microsoft Azure (App Service, Functions, DevOps, Azure OpenAI Service, API Management), while maintaining working knowledge of other cloud platforms (AWS, GCP) as needed
• Establish and document best practices for AI-assisted development workflows tailored to healthcare data and compliance requirements (HIPAA, PHI handling)
• Review AI-generated code for correctness, security vulnerabilities, adherence to software engineering principles, and maintainability before merge
• Partner with engineering leads to define guardrails for safe AI tool usage across teams
• Mentor and train other engineers on effective prompting, code review of AI output, and productivity workflows with Copilot and similar tools
• Collaborate with DevOps/platform teams to integrate AI tooling into CI/CD pipelines
• Monitor and report on productivity gains, code quality metrics, and adoption of AI-assisted workflows
• Stay current on emerging AI development tools and evaluate new tools for enterprise fit
• Architect and build autonomous agent systems capable of multi-step planning, reasoning, and tool/function calling
• Design and implement LangGraph, LangChain, Multi-Agent Systems, RAG, Prompt Engineering, Tool Calling, Workflow Orchestration, Memory Management, Vector Databases, LLM Integration
• Build RAG pipelines and integrate vector databases as a foundation for agent context and decision-making
• Implement memory and state management strategies for agents operating across multi-step, multi-turn interactions
• Design error recovery, self-correction, and human-in-the-loop escalation mechanisms for autonomous workflows
• Integrate agent systems with enterprise APIs, internal tools, and data sources (.NET and Python-based systems)
• Evaluate agent behavior for reliability, safety, task completion accuracy, and appropriate handling of healthcare data (HIPAA, PHI)
• Design and implement solutions on Microsoft Azure (Azure OpenAI Service, Azure AI Search, Azure Functions, App Service), while maintaining working knowledge of other cloud platforms as needed
• Use GitHub Copilot and other AI coding assistants to accelerate development while maintaining code quality and security standards
• Collaborate with product, data, and engineering teams to identify high-value automation opportunities suited to agentic approaches
• Stay current on emerging agent frameworks, orchestration patterns, and evaluation methodologies
• Define enterprise-wide architectural standards, patterns, and reference designs for AI solutions (LLM integration, RAG pipelines, agentic systems, vector databases)
• Lead technical evaluation and selection of AI platforms, models, and tools (Azure OpenAI Service, Azure AI Search, agent orchestration frameworks, etc.)
• Own the AI governance framework — model risk management, data privacy, HIPAA/PHI compliance, responsible AI, and security guardrails
• Architect scalable, secure, and cost-efficient AI solutions on Microsoft Azure, aligned with broader enterprise cloud strategy
• Provide technical leadership and mentorship to AI Engineers, Agentic AI Engineers, and AI-Assisted Development Specialists across teams
• Partner with engineering, security, compliance, and business leadership to align AI initiatives with organizational priorities and regulatory requirements
• Evaluate build-vs-buy decisions for AI capabilities and vendor/platform tooling
• Establish standards for AI system evaluation, monitoring, and observability (model drift, performance, safety, bias)
• Define best practices and guardrails for the use of AI coding assistants (GitHub Copilot and others) across engineering teams
• Stay ahead of the AI landscape — emerging models, frameworks, regulations, and industry practices — and translate relevant developments into actionable enterprise strategy
• Present architectural recommendations and AI strategy to senior leadership and stakeholders

Requirements:

• Bachelor's degree in computer science, Information Technology, or related field (or equivalent practical experience)
• 5+ years of professional experience in software development or IT
• 2+ years of experience working with cloud platforms and AI/ML-driven solutions, with Azure strongly preferred
• Strong full-stack development experience — front end, middle tier, and backend — with solid grounding in software engineering principles (design patterns, testing, code quality, architecture)
• Strong hands-on experience with .NET / C# and Python
• Solid understanding of cloud technologies and AI solution architecture, with emphasis on Microsoft Azure (App Service, Functions, DevOps, Azure OpenAI, API Management, or similar)
• Practical, daily experience using GitHub Copilot and/or comparable AI coding assistants
• Strong understanding of secure coding practices, especially relevant to healthcare/PHI data
• Experience with CI/CD pipelines and version control (Git, Azure DevOps, GitHub)
• Familiarity with code review processes and quality/testing standards
• Strong communication skills — able to explain technical tradeoffs of AI-assisted approaches to both engineers and non-technical stakeholders
• Adaptability and critical thinking — comfortable with ambiguity and fast-evolving tools, and able to evaluate AI-generated output rather than accept it uncritically
• 2+ years of hands-on experience building AI/LLM-powered applications, including at least 1 year working with agentic or multi-step AI systems
• Strong programming skills in .NET / C# and Python
• Hands-on experience with agent orchestration frameworks (LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar)
• Solid experience with RAG pipelines, vector databases, and embedding models
• Understanding of tool-use/function-calling architectures and multi-agent design patterns
• Solid understanding of cloud technologies and AI solution architecture, with emphasis on Microsoft Azure (Azure OpenAI Service, Azure AI Search, Functions, App Service, or similar)
• Experience debugging non-deterministic, multi-step systems
• Practical experience using GitHub Copilot and/or comparable AI coding assistants
• Strong communication skills — able to explain agent behavior, limitations, and risk tradeoffs to both technical and non-technical stakeholders
• Adaptability and critical thinking — comfortable with ambiguity in emerging frameworks, and rigorous about evaluating autonomous system behavior rather than assuming correctness
• Bachelor's degree in computer science, Information Technology, or related field
• 10+ years of professional experience in software development, cloud architecture, or IT, including significant experience in an architect or technical lead role
• 4+ years of hands-on experience designing and delivering AI/LLM-powered systems, including RAG and/or agentic architectures
• Deep expertise in cloud architecture with a strong emphasis on Microsoft Azure (Azure OpenAI Service, Azure AI Search, App Service, Functions, API Management, Azure DevOps, networking/security services), with working knowledge of AWS/GCP
• Strong background in .NET / C# and Python, with the ability to evaluate and guide architecture across full-stack systems (front end, middle tier, backend)
• Deep understanding of LLM integration patterns, RAG pipelines, vector databases, embedding models, and agent orchestration frameworks
• Strong grounding in AI governance, model risk management, and responsible/ethical AI practices
• Solid understanding of data privacy and security requirements for healthcare data (HIPAA, PHI)
• Experience defining CI/CD, DevOps, and MLOps/LLMOps practices at scale
• Familiarity with GitHub Copilot and other AI coding assistants, and how to govern their use across an enterprise
• Excellent communication and stakeholder management skills — able to influence senior leadership, engineering teams, and non-technical partners alike
• Strong mentorship and leadership presence — able to set technical direction and elevate the capabilities of engineering teams without direct authority
• Experience in a regulated industry (healthcare, insurance, or financial services) strongly preferred
• Master's degree a plus