Manager, Forward Deployed Engineering

United StatesRemoteFull-timemid

Software EngineerSoftware Engineering

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Quick Summary

Requirements Summary

At least 7 years of software engineering experience, including 2 or more years leading engineers or technical teams, ideally in distributed environments.

Technical Tools

Software EngineerSoftware Engineering

Join a data, AI, and digital engineering consultancy focused on transforming ambitious AI initiatives into practical, production-ready solutions that deliver measurable business results. As Manager, Forward Deployed Engineering, you will lead and develop a distributed team of engineers across the United States and Latin America, translating complex business challenges into scalable AI-powered systems. You will combine hands-on technical leadership with client-facing delivery, guiding architecture decisions, building prototypes, and overseeing successful implementation. Working closely with clients and cross-functional teams, you will drive the adoption of advanced AI technologies, including large language models, agentic workflows, and enterprise integrations. You will also establish reusable engineering practices, mentor technical talent, and identify opportunities to expand client engagements. This is an opportunity to shape an evolving AI engineering practice in a collaborative, fast-paced environment where technical excellence, ownership, and real-world impact are central to success.

Lead and develop a distributed engineering team: Hire, mentor, and grow forward deployed engineers across the United States and Latin America, fostering a culture of trust, accountability, collaboration, and consistent engineering standards across time zones.

Oversee client delivery: Take ownership of scope, quality, timelines, and business outcomes across multiple concurrent engagements, ensuring that AI solutions move from initial discovery to reliable production deployment.

Drive technical client engagement: Lead demonstrations, architecture discussions, and delivery workshops, helping clients understand how emerging AI development tools and agentic technologies can address their specific business challenges.

Remain hands-on technically: Contribute to prototypes, review technical designs and code, and help engineers overcome challenges involving agentic workflows, tool integrations, Model Context Protocol (MCP), and AI evaluation.

Identify growth opportunities: Recognize opportunities to extend existing engagements, collaborate with account leadership, and help define the scope and direction of subsequent project phases.

Develop reusable engineering practices: Establish technical patterns, accelerators, documentation, and playbooks that improve delivery consistency, efficiency, and quality across the distributed team.

Coordinate cross-functional execution: Partner with data, cloud, and digital engineering specialists to deliver integrated solutions that address broader client needs.

Promote responsible AI implementation: Incorporate appropriate governance, security, evaluation, and responsible-use practices into enterprise AI solutions.

Requirements

~2 min read

Professional experience: At least 7 years of software engineering experience, including 2 or more years leading engineers or technical teams, ideally in distributed environments.

Client-facing delivery: Demonstrated experience delivering technical solutions in consulting, solutions engineering, professional services, or forward deployed engineering environments.

AI and LLM expertise: Hands-on experience building applications with large language models and agentic architectures, including tool use, retrieval-augmented generation (RAG), workflow orchestration, and evaluation.

Software engineering skills: Strong proficiency in Python or TypeScript, with solid knowledge of API design, continuous integration and continuous delivery (CI/CD), and cloud platforms such as Azure, AWS, or Google Cloud Platform.

Production delivery: A proven ability to navigate ambiguous business problems, make sound technical decisions, and deliver reliable systems into production.

Communication and collaboration: Excellent written and spoken English, with the ability to explain complex technical concepts clearly to both executive stakeholders and engineering teams.

Time zone alignment: Availability for meaningful working-hours overlap with the US Eastern and Central time zones.

Preferred technical experience: Familiarity with Claude Code, Claude Cowork, the Anthropic API, or the Model Context Protocol (MCP).

Enterprise AI knowledge: Experience with AI governance, security, and responsible AI practices in enterprise environments is an advantage.

Additional qualifications: Fluency in Spanish or Portuguese, a background in data science or formal engineering education, and experience in consulting or professional services are desirable.

Leadership qualities: Strong ownership of outcomes, intellectual curiosity, the confidence to challenge assumptions constructively, and a commitment to coaching and developing others.

Distributed team management: Ability to communicate effectively through clear documentation, asynchronous collaboration, and well-defined decisions while adapting to rapidly evolving technologies.

What We Offer

~2 min read

Remote work flexibility: Remote opportunities for candidates based in the United States, with a distributed team operating across the Americas.

Technical innovation: Opportunities to work with advanced AI technologies, agentic systems, and modern engineering tools.

Leadership and career development: The opportunity to build and mentor a distributed engineering team while helping shape an expanding applied AI practice.

Meaningful client impact: Direct involvement in solving complex business challenges and bringing AI solutions into production.

Cross-functional collaboration: Exposure to multidisciplinary projects spanning AI, data, cloud, and digital engineering.

Professional growth: Opportunities to develop technical expertise, strengthen client advisory skills, and influence engineering standards and delivery practices.

Compensation: Salary details and the availability of additional benefits have not been specified in the provided job description.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1

✓Remote work flexibility: Remote opportunities for candidates based in the United States, with a distributed team operating across the Americas.

✓Technical innovation: Opportunities to work with advanced AI technologies, agentic systems, and modern engineering tools.

✓Leadership and career development: The opportunity to build and mentor a distributed engineering team while helping shape an expanding applied AI practice.

✓Meaningful client impact: Direct involvement in solving complex business challenges and bringing AI solutions into production.

✓Cross-functional collaboration: Exposure to multidisciplinary projects spanning AI, data, cloud, and digital engineering.

✓Professional growth: Opportunities to develop technical expertise, strengthen client advisory skills, and influence engineering standards and delivery practices.

✓Compensation: Salary details and the availability of additional benefits have not been specified in the provided job description.