Data Engineering Manager - Ai-First Platform Leader Remote

Félix; Ciudad de Mendoza; Remote; ARS 185,448,000 - 278,173,000; Full time

Benefits offered by this job

Professional growth

Competitive USD-based compensation

Exciting projects with Fortune 500 and

Flext

Job summary

AgileEngine is seeking a Senior AI Engineer to design and build agentic workflows and AI-powered products for enterprise customers in higher education. The role demands 5+ years in software, strong Java/Spring Boot, AI agent experience, and AWS proficiency.

You will lead end-to-end development, tooling integration, and production-ready systems in a remote LATAM setting for a 1-year engagement. The candidate should excel in multi-agent orchestration, RAG, and secure enterprise deployments, with

Qualifications

• 5+ years in a software product development environment.
• Strong Java and Spring Boot expertise.
• Hands-on AI agents/orchestration experience.
• Experience with TypeScript, Python, RESTful APIs, AWS.

Responsibilities

• Design and build agentic workflows coordinating tools, services, data, and human approvals.
• Develop reusable patterns for agent orchestration, tool use, context management, memory, and multi-agent collaboration.
• Use AI coding tools through planning, implementation, testing, debugging, and code review.
• Collaborate with product and engineering leaders to connect agentic capabilities to meaningful outcomes.

Skills

5+ years of experience in software

Java

Spring Boot

Relational databases

AI agents/orchestration

Code review/testing/release

TypeScript

Python

RESTful APIs

AWS infrastructure

APIs/workflow engines

Observability/security/failure recover

Leadership/cross-team influence

Enterprise SaaS/multi-tenant

Job description

Location: LATAM English Level: B2 B2 About the Project: technology Company

We are seeking a highly technical, hands-on Forward Deployed Engineer (FDE) / Conversational AI Architect to design, build, and deploy next-generation agentic AI systems. In this role, you will act as the engineering

bridge between frontier Generative AI models and complex enterprise production infrastructure.

You will not just design architectures; you will write production-grade code, orchestrate multi-agent workflows using Gemini CX / Vertex AI Agent Builder, maintain deterministic state machines via Dialogflow

CX, and build secure cloud data pipelines using the Advanced Agent Modeling (AAM) framework.

Key Responsibilities

• Agentic AI Architecture: Design and deploy goal-oriented, autonomous multi-agent systems utilizing Gemini CX / Vertex AI Agent Studio, moving customer touchpoints from basic deflection to true end-to-end resolution.
• Deterministic & Generative Flow Engineering: Orchestrate hybrid conversational workflows by combining generative playbooks with precise state-machine tracking in Dialogflow CX (Pages, Parameters, Conditional Routing, and Transition Routes).
• Enterprise Grounding (RAG): Build, optimize, and maintain Retrieval-Augmented Generation (RAG) pipelines using Vertex AI Search to ground agents securely in unstructured enterprise knowledge bases.
• Backend Integrations & Webhooks: Develop and deploy secure backend integrations, connectors, and webhooks using Cloud Run, Cloud Functions, and the Model Context Protocol (MCP) to link conversational layers to enterprise CRMs, ERPs, and internal databases.
• DevOps & Security Guardrails: Enforce enterprise-grade data security and compliance by implementing Model Armor constraints, configuring VPC Service Controls (VPC-SC), and enforcing strict IAM least-privilege boundaries.
• Data Piping & Telemetry: Build telemetry pipelines that stream raw conversation transcripts out of Dialogflow into BigQuery, utilizing CCAI Insights to conduct massive error-taxonomy reviews, intent health analysis, and containment rate reporting.

Must Have Skills:

Required Technical Skills & Qualifications

• Google Cloud AI Ecosystem: Deep hands-on experience with Gemini CX, Google Cloud Contact Center AI (CCAI), and the Advanced Agent Modeling (AAM) framework.
• Conversation Engineering: Proven track record in Dialogflow CX, Speech-to-Text (STT) tuning (phrase hints, audio profiles), Text-to-Speech (TTS), and telephony/SIP trunking configurations.
• Programming & Automation: Strong proficiency in Python or Node.js. Experience writing custom automation scripts or utilizing Google Cloud wrapper libraries (e.g., dfcx-scrapi) is a massive plus.
• GCP Infrastructure & DevOps: Solid experience with Cloud Run, Cloud Functions, BigQuery, Looker Studio, and Infrastructure-as-Code (Terraform).
• Security First Mindset: Practical knowledge of cloud security, data anonymization, and isolating model training perimeters within enterprise tenant constraints.
• Production Experience: A history of successfully moving generative AI agents out of the "Pilot/MVP" stage into fully scaled, live production environments facing millions of users.

Engagement Duration:

1 year

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Senior AI Engineer to design and build agentic workflows and AI-powered products for enterprise customers in higher education.

MUST HAVES

- 5+ years of experience in a software product development environment.

- Strong proficiency with Java and Spring Boot.

- Experience with relational databases.

- Hands-on experience building AI agents, tool-using LLM applications, or orchestrated workflows.

- Experience using agents to support coding, code review, testing, release management, or incident response.

- Senior-level experience building and operating production software systems.

- Experience with TypeScript, Python, RESTful APIs, and infrastructure on AWS.

- Experience with APIs, workflow engines, event-driven architectures, integrations, or distributed systems.

- Strong understanding of testing, observability, security, permissions, and failure recovery.

- Ability to turn ambiguous opportunities into practical, reliable technical solutions.

- Strong communication skills and the ability to influence engineering practices across a team.

- Experience building enterprise SaaS or multi-tenant systems.

- Leadership mindset and ability to drive changes across different teams.

NICE TO HAVES

- Experience with multi-agent systems, RAG, vector search, agent evaluation, or human-in-the-loop workflows.

- Familiarity with higher education technology and its privacy and compliance requirements.

- Experience leading technical transformation or introducing new engineering practices.

WHAT YOU WILL DO

- Design and build agentic workflows that coordinate tools, services, data, and human approvals.

- Develop reusable patterns for agent orchestration, tool use, context management, memory, and multi-agent collaboration.

- Use agentic coding tools throughout the development lifecycle, including planning, implementation, testing, debugging, refactoring, code review, and documentation.

- Integrate agents into software development, testing, deployment, support, and operational workflows.

- Establish standards for agent evaluation, observability, reliability, security, and governance.

- Prototype new agentic capabilities and turn successful experiments into production systems.

- Build complete, usable products—not just demonstrations or isolated model integrations.

- Identify opportunities to improve engineering productivity and product delivery through agentic development.

- Mentor engineers and help shape an agentic-first technical strategy across the organization.

- Collaborate with product and engineering leaders to connect agentic capabilities to meaningful outcomes.

- Demonstrate the ability to use AI coding agents as productive engineering collaborators across an application codebase.

- Provide agents with clear context, constraints, architecture, acceptance criteria, and technical direction.

- Review, test, secure, and improve agent-generated code rather than accepting outputs without verification.

- Decompose complex application work into agent-ready tasks while maintaining architectural consistency and product intent.

- Create workflows in which agents can reason, select tools, call APIs, manage state, recover from failures, and elevate to people when appropriate.

- Design agentic applications around real user needs, including intuitive experiences, reliable workflows, permissions, audit trails, and meaningful error handling.

- Move from prototype to production by addressing performance, scalability, security, monitoring, evaluation, cost, and ongoing maintenance.

- Understand problems deeply, make appropriate tradeoffs, and deliver complete solutions that customers can depend on.

PERKS AND BENEFITS

- Professional growth : Mentorship, TechTalks, and personalized growth roadmaps.

- Competitive compensation : USD-based pay with education, fitness, and team activity budgets.

- Exciting projects : Modern solutions with Fortune 500 and top product companies.

- Flext