[8GS] Senior Agentic Engineering Consultant

Software Mind Americas

22h

About The Position

This is a 3-month project. The Senior Agentic Engineering Consultant will deliver AI-forward agentic projects and priority engineering items, with primary responsibility for building and scaling a secure, reusable agentic engineering harness. The role requires production-quality implementation, measurable outcomes, a solution-oriented mindset, and effective knowledge transfer to internal teams.

Requirements

90% English written and oral (at least B2 level) with excellent communication skills.
7+ years of professional software engineering experience with senior-level design and hands-on delivery responsibility.
Demonstrated harness-engineering and loop-engineering experience, including tool calling, structured context, planning and execution loops, evaluation, recovery, self-correction, and human review.
Expert-level experience with at least one enterprise agent-based coding tool, together with strong harness-engineering experience. This includes autonomous workflows, multi-file and cross-repository implementation, test-and-fix loops, refactoring, code review, and validation of AI-generated code.
Core engineering expertise in C#/.NET, Angular, Azure SQL, API development, and OpenAPI specifications, with practical Python or TypeScript experience for agent tooling and automation.
Deep experience with Azure, Azure DevOps, Git, pull requests, YAML pipelines, CI/CD, automated testing, DevSecOps, and Playwright for browser automation and test verification.
Experience with MCP or equivalent integration patterns, including authentication, authorization, schemas, observability, error handling, and safe execution.
Strong communication, technical judgment, ownership, and a solution-oriented mindset, with the ability to translate ambiguous engineering challenges into practical, secure, and maintainable solutions while working directly with a senior technology leader.

Nice To Haves

GitHub Copilot experience is preferred.
Claude Code experience, especially for terminal-based autonomous engineering, cross-repository work, and tool-driven development workflows.
Microsoft Foundry, Copilot Studio, Microsoft 365 Copilot, Azure API Management, Azure Functions, Application Insights, Key Vault, Service Bus, or Cosmos DB.
.NET modernization, SAST/Snyk, contract testing, evaluation harnesses, golden test sets, agent benchmarks, AI cost controls, enterprise change management, privacy, security, architecture governance, and production support.

Responsibilities

Design and implement agentic harnesses and loop-engineering workflows covering context loading, planning, coding, tool execution, testing, validation, recovery, self-correction, and human review.
Design, code, test, and maintain skill files, tool definitions, prompts, schemas, personas, repository instructions, and reusable components for the agentic harness across product, development, architecture, and quality workflows.
Engineer MCP servers and integrations with Azure DevOps, repositories, pipelines, engineering standards, and approved enterprise knowledge sources; build and maintain Playwright as the test-verification harness and tool for agentic workflows.
Diagnose and fix application exceptions, production defects, and security vulnerabilities; implement durable code corrections, automated tests, and validated remediation.
Deliver production-quality applications, APIs, services, and automation using C#/.NET, Angular, Azure SQL, Python or TypeScript, Azure, Git, Azure DevOps, and CI/CD.
Use an advanced agent-based coding tool for autonomous and multi-step delivery, multi-file and cross-repository changes, modernization, refactoring, test-and-fix loops, code review, and documentation.
Implement quality, security, and governance controls including automated tests, protected-branch approvals, least privilege, secrets management, traceability, prompt-injection defenses, and safe tool execution.
Instrument agent runs and delivery outcomes for quality, reliability, cycle time, rework, cost, tool use, and human intervention.
Work directly with the Sr. Director to convert priorities into an executable backlog, apply a solution-oriented mindset to ambiguous engineering challenges, demonstrate progress, document standards, and transfer knowledge to the current engineering team.