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Nimble Gravity

Director, Forward Deployed Engineering

LATAM, United States

Location
LATAM, United States
Work
Remote
Employment
Not stated
Level
Director
Function
Engineering
Pay
Not stated
Posted
2 weeks ago

Pay and the market here

4 engineering jobs open in LATAM: 100% remote, 2 posted in the last 30 days.

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About the role

About Nimble Gravity

We’re a data, AI and digital engineering consultancy. Certified across Microsoft, Anthropic, and Databricks, we turn AI ambition into working systems for leaders who need results, not roadmaps.

We're looking for a hands-on engineering leader who is as comfortable in a client workshop as in a pull request. You'll build and coach a team that turns ambiguous business problems into working AI systems in production. You'll also spot where the next phase of work lives.

Key Responsibilities

  • Lead the team: Hire, coach, and grow forward deployed engineers. Set a high bar for technical quality, client communication, and ownership.
  • Own delivery: Be accountable for scope, quality, timelines, and outcomes across multiple concurrent client engagements.
  • Be the technical voice with clients: Run demos, architecture sessions, and delivery workshops that show clients what Claude Code and Claude Cowork can do in their environment.
  • Build alongside the team: Stay close to the code. Prototype, review designs, and unblock the team on agentic workflows, tool use, MCP integrations, and evaluation.
  • Find the next phase: Spot expansion opportunities in the work and partner with account leadership to shape and scope them.
  • Establish repeatable practices: Build reusable patterns, accelerators, and playbooks so every engagement starts further ahead than the last.
  • Collaborate across the business: Work with data, cloud, and digital engineering teams to deliver end-to-end outcomes.

What We're Looking For

Required

  • 15+ years in software engineering, with 5+ years leading engineers or technical teams.
  • Experience in client-facing delivery: consulting, solutions engineering, or forward deployed work.
  • Hands-on experience building with LLMs and agentic patterns, including tool use, RAG, workflow orchestration, and evaluation.
  • Strong Python or TypeScript skills, plus solid API design, CI/CD, and cloud fundamentals (Azure, AWS, or GCP).
  • Proven ability to explain complex technical ideas clearly to executives and engineers alike.
  • A track record of taking ambiguous problems to production.

Preferred

  • Hands-on experience with Claude Code, Claude Cowork, the Anthropic API, or the Model Context Protocol.
  • Experience with AI governance, security, and responsible-use practices in enterprise settings.
  • Background in data science or formal engineering training.
  • Experience in a consulting or professional services environment.

Core Qualities

  • Ownership: You take responsibility for outcomes, not just tasks.
  • Curiosity and courage: You ask the real questions and challenge assumptions, politely but firmly.
  • Coaching mindset: You grow people and share credit.
  • Adaptability: You're comfortable when the tools change monthly.
  • Pragmatism: You ship what works.

Interview process

Interview with Recruiter (30 min)

1st Technical Interview (45 min)

2nd Technical Interview (45 min)

Final Interview with VP, AI Applied Solutions

Case Studies

Nimble Gravity Applied Anthropic Practice

About Nimble Gravity

Nimble Gravity is a team of outdoor enthusiasts, adrenaline seekers, and experienced growth hackers. We love solving hard problems and believe the right data can transform and propel growth for any organization.

Nimble Gravity is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Nimble Gravity considers all qualified applicants.

Source

Posted by Nimble Gravity on their own hiring page, job-boards.greenhouse.io. OptiTalent shows it as published, read 07 Nov 2026 11:48 UTC; the original is the reference.

View the original ad ↗

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