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 Adecuado 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

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📌 Senior Full stack Engineer (Ciudad de México)
🏢 fulcrumdigital
📍 Ciudad de México