Senior Full stack Engineer

fulcrumdigital; Ciudad de México; Presencial; MXN 1.500.000 - 2.500.000; Jornada completa

Descripción de la vacante

fulcrumdigital is seeking a hands-on senior technical leader to design and ship AI-enabled, agentic applications at scale. You will own architecture across cloud-native services, ensure security, observability, and reliable delivery in production environments.

You will mentor engineers, shape roadmaps, collaborate with product and data science, and drive the SDLC with modern AI tooling, testing, and governance to accelerate value for customers.

Formación

• Experience building scalable, secure production systems.
• Hands-on AI-powered products or agentic applications experience with LLMs and tooling.
• Strong understanding of agentic system design, planning, reasoning, and human-in-the-loop controls.
• Experience taking AI solutions from prototype to production with reliability, observability, latency, cost, security, and governance.
• Experience with modern AI frameworks, SDKs, and tooling for building AI applications and developer productivity.

Responsabilidades

• Lead hands-on architecture, design, and implementation of AI-enabled services from concept to production.
• Define engineering patterns and best practices for production AI systems with guardrails and cost control.
• Drive end-to-end software delivery across the SDLC from discovery to production operations.
• Maintain code quality and documentation while accelerating design, coding, testing, and delivery.

Conocimientos

Architectural leadership

Agentic AI design

Java programming

Cloud-native design

Frontend design with React/Next.js

Herramientas

React

Next.js

Kubernetes

AWS

Azure

Descripción del empleo

Position Responsibilities

• Lead hands-on architecture, design, and implementation of agentic applications, AI-powered services, and platform capabilities from concept through production
• Define engineering patterns and best practices for production AI systems, including evaluation, monitoring, guardrails, resiliency, cost control, and rollback strategies
• Drive end-to-end software delivery across the SDLC, from discovery and prototyping to testing, release, and production operations
• Use engineering tools to accelerate design, coding, testing, documentation, troubleshooting, and delivery while maintaining strong engineering judgment and code quality standards
• Champion an AI-enabled SDLC by improving developer workflows, automation, test generation, code review quality, release confidence, and team productivity
• Partner closely with Product, Applied AI, Data Science, and business stakeholders to translate ambiguous opportunities into scalable product capabilities
• Provide technical leadership through architectural decisions, design reviews, code reviews, hands-on contribution, and mentoring of engineers across the team
• Build highly available, secure, and maintainable cloud-native services with strong observability, performance, and operational readiness
• Shape technical roadmaps, identify short- and long-term platform needs, and influence architecture choices that enable scale, reuse, and faster delivery
• Collaborate across teams and business units to solve complex business and engineering problems with practical, high-impact solution
• Keep senior stakeholders informed of progress, risks, trade-offs, and implementation decisions in a clear and concise manner

Requirements Ideal Candidate Qualifications

• Strong software engineering experience building scalable, secure, maintainable production systems, including experience leading complex technical initiatives end to end
• Hands-on experience building and shipping AI-powered products or agentic applications using LLMs, orchestration frameworks, tool-calling patterns, retrieval, and context-aware workflows
• Strong understanding of agentic system design, including planning, reasoning loops, workflow orchestration, memory, grounding, evaluation, safety, and human-in-the-loop controls
• Experience taking AI solutions from prototype to production with sound engineering discipline around reliability, observability, latency, cost, security, and governance
• Experience with modern AI frameworks, SDKs, and tooling for building AI applications, agent workflows, and developer productivity use cases
• Strong programming skills in one or more backend languages such as Java 17+, and Python, with the ability to write high-quality, well-tested, production-ready code
• Experience with modern front-end frameworks such as React and/or Next.js for building intuitive product experiences would be beneficial
• Experience building services in cloud-native environments using Kubernetes and managed cloud services on AWS, Azure
• Good understanding of APIs, distributed systems, event-driven architectures, data pipelines, and integration patterns across enterprise platforms
• Experience with CI/CD, automated testing, and engineering automation, including the ability to improve SDLC efficiency and release quality using AI tools
• Practical experience using AI coding and engineering assistants to improve productivity across design, implementation, testing, debugging, documentation, and operational support
• Strong background in software security, including authentication, authorisation, secrets management, encryption, threat modelling, and secure deployment practices for AI-enabled systems
• Proven ability to create reusable platforms, frameworks, or internal engineering capabilities that improve developer experience and accelerate delivery across teams
• Strong product mindset with the ability to translate user needs and business goals into practical, high-impact technical solutions
• Excellent collaboration and communication skills, with experience influencing across engineering, product, data science, and leadership stakeholders

Requirements Bucket Skills / Metrics Must-Have

• Strong hands-on programming expertise in Java and Python, with the ability to design, build, test, and optimise production-grade backend services
• Strong experience with React for building modern, responsive, and intuitive user interfaces for enterprise applications
• Experience with Next.js or modern front-end architecture patterns alongside React
• Deep experience building cloud-native applications using containers, Kubernetes, microservices, and managed cloud services in AWS and/or Azure
• Strong expertise in designing and building APIs, including RESTful services, service contracts, versioning, security, and integration patterns
• Proven experience with event-driven architecture, asynchronous messaging, streaming, and resilient distributed system design
• Practical experience using AI tools to improve engineering productivity across coding, testing, debugging, documentation, and release workflows
• Strong understanding of software engineering quality metrics such as code quality, test automation, reliability, performance, observability, and maintainability

Good to Have

• Experience building agentic applications or AI-powered systems using LLMs, orchestration frameworks, retrieval, tool calling, and workflow automation
• Experience with API gateway, service mesh, and enterprise integration patterns
• Experience with Kafka, event streaming platforms, or large-scale messaging ecosystems
• Exposure to CI/CD automation, infrastructure as code, and release engineering practices
• Experience in regulated enterprise environments where security, governance, compliance, and auditability are critical
• Ability to mentor engineers and influence architecture, engineering standards, and developer productivity at team level

All About You

• You are a hands-on technical leader who enjoys building and shipping real products, not just prototypes
• You have experience building or operating AI-enabled or agentic applications in production and understand what it takes to make them secure, reliable, and useful at scale
• You combine strong software engineering fundamentals with curiosity and good judgment in applying emerging AI capabilities to real business problems
• You actively use AI to enhance your own engineering productivity and help teams adopt better ways of designing, coding, testing, documenting, and operating software
• You understand where AI can accelerate delivery and where human review, engineering discipline, and thoughtful controls remain essential
• You care deeply about customer value, developer experience, quality, resilience, and long-term maintainability
• You are comfortable working in collaborative, cross-functional, and internationally distributed teams
• You raise the bar for others through mentorship, technical leadership, and a practical, delivery-focused mindset
• You communicate complex technical concepts clearly and effectively to both engineering teams and senior stakeholders