Full-Stack Engineer (Ai-Enabled)

Momento Usa; México; Presencial; MXN 1.693.000 - 2.445.000; Jornada completa

Descripción de la vacante

Momento USA LLC is hiring a Full-Stack Engineer (AI-Enabled) in Mexico to build production-grade AI agents and services using TypeScript, Python, and AWS serverless. You will design agent behaviors, implement sandboxing and safeguards, and write thorough evals for AI-driven changes.

The role emphasizes observability, reliability, and collaboration across teams. You will refine pipelines, leverage Terraform for infra, and review AI-written changes for security and quality.

Formación

• Proficient in production TypeScript and Node.js environments.
• Experience with AWS Lambda, Step Functions, DynamoDB, Bedrock or similar AI platforms.
• Ability to read and review AI-generated code with a focus on security and maintainability.

Responsabilidades

• Build and run production AI agents and services on AWS.
• Design agent behavior and enforce it with code.
• Sandbox and constrain agents with read-only runtimes and budget guards.
• Write evals for AI-driven code and calibrate models.
• Make agents observable with metrics, logs, and alarms.

Conocimientos

Communication

English fluency

Team collaboration

Herramientas

TypeScript

Python

AWS serverless

Terraform

NoSQL/SQL databases

GitLab CI/CD

React

GraphQL

Java

Spring Boot

Kubernetes

Descripción del empleo

• Build and run production AI agents: develop TypeScript agents and services on AWS (Lambda, Step Functions, DynamoDB, Bedrock) using Strands or LangGraph and AI SDKs.
• Design agent behavior: decide what the model investigates and what plain code enforces.
• Sandbox and constrain agents: build read-only runtimes, scoped tool access, worktree-contained reads, and budget and timeout guards that hold when the model misbehaves.
• Write evals for everything AI-driven: build golden sets and replays from real production cases, calibrate judges, and gate changes on recall, precision and false-positive rate. Run model and effort-level comparisons before a change ships.
• Make agents observable: emit reason-coded metrics and structured logs and write alarms that fire on real failures. Investigate production misses in Splunk and VictoriaMetrics.
• Run infrastructure and pipelines: maintain Terraform roots across environments under our tagging and permission-boundary rules, and improve GitLab CI/CD for build, test, deploy and quality gates.
• Handle integrations that survive retries, rate limits, permanent delivery failures and stale state.
• Use AI to write and review most code, and keep agent context current.
• Review AI-written changes rigorously: check security, correctness and maintainability, and catch what the tests don't.
• Enable other teams: set up assistant configuration, skills, hooks and MCP servers, pair with engineers, and turn what works into reusable practice.
• Build the surfaces agents need: React and API work for review summaries, dashboards and internal tooling, preferring output that agents, CLIs and Slack can read.
• Document how it works: sequence and architecture diagrams, runbooks, and short decision records that explain why.

Requirements:

• LLM features in production: has shipped features on LLM APIs (prompts, tool calling, structured output, long context) and can describe the eval that gated release, what failed and what changed.
• TypeScript: strong production TypeScript and Node, including async code, testing and monorepo tooling.
• Python: working proficiency for evals, analysis and scripting.
• AWS serverless: Lambda, Step Functions, DynamoDB, IAM and event-driven design, plus Bedrock.
• Infrastructure as code: able to read and change Terraform safely across environments.
• Data: hands-on experience with NoSQL and SQL stores, including schema changes and migrations on live systems.
• Observability: able to design metrics, logs and alarms for something non-deterministic, and to debug it from them.
• CI/CD: proficiency with CI/CD tools, ideally GitLab CI/CD.
• AI-assisted development: daily use of an AI coding assistant, with the discipline to verify what it produces.
• Communication: fluent written and spoken English, and the ability to explain a trade-off and get a team to adopt an approach.

Nice to have:

• Multi-agent systems, MCP servers or evaluation frameworks (for example Strands Evals).
• LLM cost control: model routing, prompt caching, token budgets.
• Prompt-injection defense and agent security.
• React and GraphQL for internal tools.
• Java and Spring Boot, for reading or integrating with existing services.
• Code intelligence or retrieval work (indexing, symbol search, knowledge bundles).
• Kubernetes, AWS AppSync and EventBridge.

Note: Momento USA is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

Full-Stack Engineer (AI-Enabled) Mexico