Forward Deployed AI Architect – LatAm IRC299908

GlobalLogic; Argentina; Presencial; ARS 1.800.000 - 3.000.000; Jornada completa

Descripción de la vacante

GlobalLogic in Argentina is seeking a Forward Deployed AI Architect to bridge core AI platform capabilities with enterprise client workflows. You will write production code, design architectures, and lead engineering transformation across SDLC into an AI-Driven Software Development Lifecycle.

This senior role requires 15+ years in software leadership, hands‑on AI experience, and the ability to influence executive stakeholders.

Formación

• 15+ years in software engineering or related leadership roles.
• Hands-on experience delivering enterprise software at scale.
• Experience with enterprise customer transformations.
• Proven ability to build production‑grade AI agents and multi‑agent systems.
• Practical expertise in AI across the software lifecycle, not just prompt engineering.

Responsabilidades

• Lead AI‑driven software transformation for clients.
• Define transformation roadmaps, governance, and AI‑native SDLC.
• Design multi‑agent systems and autonomous engineering workflows.
• Collaborate with CIOs/CTOs and engineering leaders to influence decisions.
• Deliver measurable business outcomes and ROI for client programs.

Conocimientos

Software engineering

Architectural leadership

AI engineering mindset

Hands-on coding

Enterprise software

SDLC to AI‑DLC transformation

Herramientas

Claude Code

Cursor

OpenAI Codex

GitHub Copilot

Google Cloud Code

Windsurf

Antigravity

LangChain

AutoGen

Semantic Kernel

LlamaIndex

CrewAI

MCP

Descripción del empleo

Forward Deployed AI Architect – LatAm IRC299908

Function

Engineering

Experience

15+ years

Location

Argentina - Buenos Aires

Skills

Autogen, Claude code, Cursor, Google Antigravity, langchain, llamaindex, MCP, openai, RAG, semantic kernel, Vector Databases (AI/RAG)

Department/Project Description
We are seeking a Forward-Deployed AI Product Architect to work at the intersection of core product engineering, AI orchestration, and high-impact client deployment. In this role, you will bridge the gap between our core AI platform capabilities and the highly regulated, complex workflows of our enterprise clients

Requirements

Role Summary
We are looking for an exceptional Principal AI Acceleration Architect (Forward Deployed AI Engineer) who can work directly with enterprise customers to transform software engineering using AI.
This is not a traditional Solution Architect or AI Consultant role. We are looking for someone who is equally comfortable writing production code, building autonomous AI agents, designing enterprise architectures, influencing executive stakeholders, and leading engineering transformation.
You will work alongside customer engineering and product teams to redesign the Software Development Lifecycle (SDLC) into an AI-Driven Software Development Lifecycle (AIDLC)—leveraging AI coding assistants, agentic workflows, autonomous engineering loops, and intent-driven software delivery.
The ideal candidate is a builder first, architect second, and advisor third.

Key Responsibilities

• – AI-Led Software Engineering Transformation
• – Partner with customer engineering, product, architecture, platform, and executive leadership to identify opportunities for AI-driven engineering acceleration.
• – Assess existing SDLC maturity and define transformation roadmaps toward AI-native engineering organizations.
• – Design AI-first engineering operating models covering planning, development, testing, deployment, governance, and operations.

Build Production-Ready AI Solutions

• – Design, build, and deploy production-scale AI agents—not proofs of concept.
• – Develop end-to-end autonomous engineering workflows using modern AI development frameworks.
• – Build systems capable of generating plans, code, tests, documentation, reviews, and deployment artifacts with human governance.
• – Drive Intent-Driven Software Delivery
• – Help customers evolve from:

Champion concepts including:

• – Software Defined Development (SDD)
• – Intent Driven Engineering
• – Agentic Software Delivery
• – AI-native SDLC
• – Autonomous Delivery Loops
• – Customer Advisory

Work directly with:

• – CIOs
• – CTOs
• – Chief Architects
• – Engineering Leaders
• – Product Leaders

Present:

Architecture
Technical strategy
Transformation roadmap
Business outcomes
ROI
Adoption models
Challenge assumptions and influence executive decisions using first-principles thinking.

Define Measurable Outcomes

Scale Engineering Excellence

Help customers operationalize AI engineering by defining:

• – Governance
• – Security
• – Human-in-the-loop controls
• – AI observability
• – Platform architecture
• – Organizational operating model
• – Engineering metrics
• – Change management

Job responsibilities

Required Qualifications

Experience

• – 15+ years in software engineering, architecture, product engineering, platform engineering, solution architecture, or related technical leadership roles.
• – Significant hands‑on experience delivering enterprise software products at scale.
• – Experience working directly with enterprise customers in complex transformation engagements.
• – Proven track record of building production‑grade engineering platforms—not just prototypes.
• – Experience working across multiple customer environments and engineering archetypes.
• – AI-First Engineering Mindset
• – The successful candidate should be able to independently:
• – Build production‑grade AI agents end‑to‑end.
• – Design multi‑agent systems.
• – Build autonomous engineering workflows.
• – Implement intent‑driven software delivery.
• – Apply AI across the complete software lifecycle.
• – This role expects practical expertise—not prompt engineering.

Technical Expertise

Hands‑on experience with modern AI engineering platforms including several of:

• – Coding Platforms
• – Claude Code
• – Cursor
• – OpenAI Codex
• – GitHub Copilot
• – Google Cloud Code
• – Windsurf
• – Antigravity
• – Agent Frameworks
• – LangChain
• – AutoGen
• – Semantic Kernel
• – LlamaIndex
• – CrewAI
• – Model Context Protocol (MCP)

AI Engineering

• – Retrieval Augmented Generation (RAG)
• – Vector Databases
• – Evaluation Frameworks
• – Prompt Engineering
• – Tool Calling
• – Function Calling
• – Multi‑agent orchestration
• – AI Observability

Leadership Expectations

• – We are looking for individuals who:
• – Influence without authority.
• – Challenge customer assumptions constructively.
• – Simplify complex technical concepts.
• – Drive alignment across business and engineering.
• – Lead through technical credibility.
• – Build trust quickly with customer teams.

Doer Mindset

This role requires builders—not reviewers.

The ideal candidate:

• – Writes code every week.
• – Builds working systems personally.
• – Reads research papers continuously.
• – Experiments with emerging AI tooling.
• – Learns rapidly.
• – Removes delivery blockers regardless of ownership.
• – Has no ego around titles or hierarchy.
• – Leads from the front.

Customer Discovery Skills

Candidates should demonstrate the ability to:

• – Understand a customer’s business within 48 hours.
• – Identify engineering bottlenecks rapidly.
• – Connect business outcomes with technical transformation.