{"id":1597320,"url":"https://alion.io/job/globant-senior-architect-net-agentic-ai","title":"Senior Architect - .Net Agentic AI","company":{"id":61174,"name":"Globant","domain":"globant.com","url":"https://alion.io/company/globant","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"C","score":62,"open_postings":73,"ghost_share":0.548,"stale_share":0,"repost_share":0.014,"time_to_fill_p50_days":69,"computed_at":"2026-10-21T05:46:15Z"}},"role":"Backend","role_family":"Backend","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India","Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":31000,"max_usd":77000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":25},"experience_years_min":14,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Claude","optional":false},{"name":"Copilot","optional":false},{"name":"Docker","optional":false},{"name":"Kubernetes","optional":false},{"name":"OpenAI Codex","optional":false},{"name":".NET","optional":true},{"name":"Angular","optional":true},{"name":"Azure AKS","optional":true},{"name":"C#","optional":true},{"name":"CI/CD","optional":true},{"name":"Claude Code","optional":true},{"name":"Cline","optional":true},{"name":"Cursor","optional":true},{"name":"JavaScript","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"Machine Learning","optional":true},{"name":"React.js","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-02-12T12:44:08Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-21T11:58:12Z","board_verified":true,"closed_at":null,"days_open":251,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":250},"description":"Senior Software Architect - Senior AI Software Engineering Expert\nWe are a digitally native company that helps organizations reinvent themselves and unleash their potential. We are the place where innovation, design and engineering meet scale.Globant is 20 years old, NYSE listed public organization with more than 30,000 employees worldwide working out of 36 countries globally.\nwww.globant.com\nJob Description:\nLocation: Bangalore - Whitefield, Pune - Hijewadi phase - I OR Magapatta\nExperience: 14-18 Years\nPrimary Technical Skills: . NET Core technologies, Azure, Docker, Kubernetes,\nAI, AgentiAI, AI coding tools (like GitHub Copilot, Claude, Codex)\nMicroservice Architecture, Project Governance\nEnd to end solutioning, proposals, estimation.\nGood To Have : RFP, Presales, Proposals, estimation.\nWe are looking for a highly experienced software engineering expert who combines strong architecture and implementation skills with practical, disciplined use of AI-assisted development tools.This is not a generic \"prompting\" role. We need someone who can work across architecture, implementation, review, testing, and delivery, while also training other engineers to use AI in a controlled, repeatable, and production-ready way.\nThe successful candidate will help teams move beyond ad hoc AI usage. They will introduce and coach engineers on a structured AI-assisted engineering workflow that includes planning before implementation, clear constraints, reusable prompting patterns, visible review, validation, and traceability from requirements to delivered code.\nYou should be equally comfortable writing production code, reviewing system design, improving developer workflows, and coaching engineers on how to use tools such as Cursor, GitHub Copilot, Claude Code, Cline, or similar platforms responsibly and effectively.\nWhat You Will Own\nLead hands-on software engineering work across design, implementation, refactoring, testing, and delivery for cloud-based business applications.\n\nShape solution architecture for scalable, secure, maintainable platforms, with a strong focus on .NET, Azure, APIs, and distributed systems.\n\nDefine and roll out a practical AI-assisted engineering methodology that teams can reuse across projects.\n\nTrain engineers to use AI with discipline, not just speed, including how to plan work, constrain execution, review outputs, validate results, and maintain traceability.\n\nCreate reusable prompts, templates, working agreements, commands, or playbooks that reduce inconsistent one-off prompting.\n\nCoach teams on how to break work down into structured execution flows such as feature-by-feature, layer-by-layer, or parallelised implementation where appropriate.\n\nReview AI-generated plans, code, and artifacts for correctness, maintainability, architecture fit, naming, file placement, dependencies, error handling, and operational impact.\n\nEstablish quality checks so AI-assisted output is validated through tests, reviews, and requirement-based verification rather than accepted at face value.\n\nSupport modernisation initiatives, including migration from legacy solutions to modern cloud-native platforms.\n\nContribute to DevOps, CI/CD, observability, operational readiness, and engineering governance.\n\nHelp teams adopt a delivery model where AI usage is reviewable, explainable, and aligned with enterprise standards.\n\nAI Engineering Expectations for This Role\nYou must be able to teach and model a controlled AI-SDLC approach, including:\nPlanning before implementation rather than jumping straight into code generation.\n\nIterative refinement of plans based on review and feedback.\n\nClear constraints for AI execution, including requirements, architecture decisions, coding rules, file references, and expected outputs.\n\nUse of reusable prompts, commands, skills, or playbooks instead of relying on informal ad hoc instructions.\n\nStructured execution strategies that make AI work easy to follow and review.\n\nVisible review of AI-generated code and artifacts, with clear reasoning about what is accepted, rejected, or changed.\n\nValidation through tests, automated checks, and requirement-level inspection.\n\nTraceability between requirements, plan items, files changed, and implementation outcomes.\n\nThis role requires someone who can train others in these practices, inspect whether they are being followed, and raise the maturity of the engineering organisation over time.Key Responsibilities\nDeliver high-quality production code and architecture contributions in a hands-on capacity.\n\nPartner with product, architecture, and engineering teams to define practical AI-enabled ways of working.\n\nRun workshops, coaching sessions, and pairing sessions to train engineers on effective AI-assisted software delivery.\n\nCreate examples, reference implementations, and reusable artifacts that teams can adopt directly.\nEvaluate AI development tools, workflows, and guardrails through technical proof-of-concepts.\n\nDefine what good looks like for AI-generated plans, code reviews, validation evidence, and traceability outputs.\n\nReview and improve engineering practices covering design quality, coding standards, testing, deployment readiness, and maintainability.\n\nSupport observability, monitoring, automation, and operational readiness as part of the full delivery lifecycle.\n\nHelp teams make sound technical decisions and retain human control over important architectural and product-impacting choices.\n\nRequired Experience\n14+ years of experience in software development, technical architecture, or full-stack engineering.\n\nStrong hands-on experience with .NET Core / .NET, C#, Azure, and cloud-native application design.\n\nExperience designing and delivering distributed systems, API-based solutions, and integration-heavy platforms.\n\nDemonstrated practical experience using AI-assisted development tools in real engineering work, not only experimentation.\n\nProven ability to define or improve engineering workflows across planning, coding, testing, review, and release.\n\nExperience coaching, mentoring, or training engineers on technical practices, developer tooling, or delivery methods.\n\nStrong understanding of software design principles such as SOLID, DDD, OOP, and common design patterns.\n\nExperience with CI/CD, DevOps practices, code review, testing strategies, and production support.\nAbility to assess AI-generated output critically and explain trade-offs, risks, and corrective actions.\nStrong communication skills and ability to work effectively with cross-functional teams\n\nPreferred Experience\nExperience establishing engineering standards, playbooks, or governance for AI-assisted development.\n\nExperience creating reusable prompt libraries, command systems, templates, or developer enablement assets.\n\nExperience in observability, monitoring, and alerting solutions.\n\nExposure to frontend technologies such as Angular or React.\n\nExperience with Kubernetes / AKS.\n\nExperience supporting legacy-to-modern platform migration.\n\nAzure certifications such as AZ-305 or AZ-104.\n\nWhat Strong Candidates Will Demonstrate\nThey can show how they use AI to accelerate delivery without losing architectural control or engineering quality.\n\nThey can explain how they plan work before implementation and how they refine that plan during execution.\n\nThey can show examples of constraining AI with clear requirements, file references, coding rules, and expected outputs.\nThey can demonstrate a repeatable workflow for AI-assisted delivery rather than relying on one-off prompting.\nThey can explain how they review AI-generated code, validate it, and connect implementation results back to requirements.\n\nThey are capable of teaching these practices clearly and raising the capability of other engineers.\n\nWhy This Role Matters\nWe are looking for someone who can improve software delivery in two ways at the same time: by contributing directly as a senior engineer and by helping the wider team adopt a disciplined, scalable, and auditable way of working with AI.\nAt Globant, we believe in fostering a diverse and inclusive workplace where everyone feels valued and respected. We are an Equal Opportunity Employer committed to creating a thriving and inclusive environment for all employees and candidates, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other legally protected characteristic. If you need any assistance or accommodations due to a disability, please let us know by applying through our Career Site or contacting your assigned recruiter.\nWe may use AI and machine learning technologies in our recruitment process. Compensation is determined based on skills, qualifications, experience, and location. In addition to competitive salaries, we offer a comprehensive benefits package. 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