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Forward Deployed Engineer

Job in Los Angeles, Los Angeles County, California, 94199, USA
Listing for: Codos
Full Time position
Listed on 2026-10-20
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Backend Developer
Salary/Wage Range or Industry Benchmark: 150000 - 210000 USD Yearly USD 150000.00 210000.00 YEAR
Job Description & How to Apply Below

Company

Description:

Codos is an AI transformation company that helps enterprise and midsize organizations become AI-native and realize financial impact within months. By combining strategic expertise similar to top consulting firms with cutting-edge AI research and engineering, Codos delivers practical, software-driven transformation. The company focuses on AI-transformation-as-software, enabling clients to quickly integrate AI into core operations. Team members work on high-impact initiatives that directly influence business outcomes.

Codos offers a dynamic environment for professionals who want to shape how businesses adopt and scale AI.

Role

Description:

The Forward Deployed Engineer is a full-time, remote role responsible for building and deploying AI-powered software solutions directly within client environments. In this role, you will collaborate with client stakeholders and internal teams to understand business requirements, design technical architectures, and implement robust back-end systems and services. You will develop, test, and maintain production-quality code, integrate AI models and APIs, and ensure reliability, scalability, and performance of deployed solutions.

Day-to-day work includes troubleshooting issues, optimizing systems, and iterating quickly based on client feedback. You will also contribute to internal product development based on your client experiences and development of best practices that improve future deployments.

What You'll Work On:

  • Owning the technical deployment of Codos Virtual Chief AI Officer and Company Brain, from kickoff and system setup to daily use by the client’s teams
  • Connecting approved sources such as Slack, email, calls and documents to Company Brain, configuring access and checking that its answers reflect the client’s business
  • Setting up Virtual Chief AI Officer around the client’s goals and workflows, validating diagnostic findings and turning prioritized opportunities into a build plan
  • Building and evaluating agents, MCP servers, skills and integrations that use Company Brain to run workflows across finance, sales, support, HR and engineering
  • Working with function heads to get those workflows into daily use, resolve deployment issues and review the results
  • Turning the integrations, skills and deployment patterns you build repeatedly into reusable parts of the platform

Ideal Profile:

  • Previously worked on applied AI in-house, in an AI practice at a consultancy, or at an AI deployment company
  • Worked at a Speedrun, YC or other early-stage startup
  • Has a proven AI implementation success case that delivered $1M+ in impact

What You Bring to the Table:

  • You have deployed AI systems inside companies and owned the integrations, access setup and work needed to get people using them
  • You are a strong engineer who has led technical delivery for demanding customers, as a founder or CTO, a forward deployed or solutions engineer, or an engineering lead
  • You can explain an architecture to a CTO and a trade-off to a CFO on the same day
  • You get things done inside a large client where nobody owes you access, data or time
  • You have built a function or a client practice from nothing, not taken over a running one
  • You can carry one or two clients at a time and travel for kickoffs and key moments

Why You Should Join Our Team: Today a handful of people carry all client work, and every client is a multi-year relationship with direct access to the CEO and the executive team. You will be one of the first forward deployed engineers, so the playbook, the tooling and the way this function works will be shaped by you. You will shape how our product is installed, trusted and used inside a company.

The integrations, skills and deployment patterns you develop feed back into the platform,…

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