Role Description
*Engagement: Hourly / part-time, ongoing or full-time*
About the Role
We're looking for a Lead Forward Deployed Engineer to run one of these engagements end to end. This isn't an architecture-from-a-distance role — you'll sit shoulder to shoulder with a pod of 2–4 engineers, write code yourself, make the calls that keep delivery moving, and act as the person who turns an ambiguous ask into a shipped product. You'll carry the outcome for the whole pod, not just your own commits, and you'll spend most of your week building rather than managing from a distance.
Your Mission
- Own delivery for one active client engagement at a time, from first conversation to production
- Lead and grow a pod of 2–4 forward-deployed engineers
- Translate ambiguous business needs into a scoped, testable delivery plan
- Keep the client's trust by shipping — consistently, visibly, on time
- Bring AI-assisted development practices into daily delivery work
Key Responsibilities
*Delivery & Technical Leadership*
- Lead a pod of engineers through end-to-end delivery of a single project, from problem framing to production hand-off
- Write production-ready code as a hands-on contributor, not just a reviewer
- Make day-to-day technical decisions — frameworks, data models, deployment targets — and escalate architectural calls when needed
- Run code reviews and pairing sessions that raise the team's technical bar
- Use AI-assisted development tools (Copilot, Claude, ChatGPT, and similar) to accelerate delivery, and bring what works back to the wider engineering team
*Stakeholder & Client Management*
- Partner directly with business leaders, domain experts, and client stakeholders to understand needs and shape scope
- Represent the pod in status reviews, demos, and retrospectives
- Identify risks, dependencies, and blockers early — and drive the team through them
*Team & Knowledge Building*
- Mentor engineers through pairing, feedback, and targeted coaching on craft and consulting skills
- Document design decisions and reusable components to support future engagements
- Stay current with emerging AI tools and development practices, and pilot their adoption within your project
What We're Looking For
*Must Have*
- 8+ years in software development, systems integration, or technical consulting, with recent hands-on delivery experience
- 2+ years leading the technical side of a shared project — as a tech lead, team lead, or senior engineer
- Advanced proficiency in at least one modern language (Python, TypeScript, JavaScript, Go, Java, or similar)
- Solid grounding in software architecture, API design, data modeling, and full-stack or backend delivery
- Fluency in at least one major cloud platform (AWS, Azure, or GCP) and modern practices — CI/CD, containers, version control, testing
- Hands-on experience applying AI tooling (Copilot, Claude, ChatGPT, vector search, prompt engineering, RAG) in real delivery work
- Track record of shipping production software on tight timelines in a consultative or embedded setting
- Experience mentoring engineers and running effective code reviews
- Strong communication skills — able to translate technical tradeoffs for non-technical stakeholders
*Nice to Have*
- Experience delivering AI, automation, or data-intensive applications in an enterprise environment
- Experience working within large, decentralized, or multi-site organizations
- Prior experience as a forward-deployed engineer, solutions engineer, or delivery consultant
- Cloud architecture or AI/ML certification (AWS, Azure, GCP, or equivalent)
Why You'll Love This Role
- Real ownership: one engagement, full accountability, direct client contact — no layers of hand-off
- A working lead role — you build alongside your team, not just manage it
- Room to bring modern AI-assisted tooling into how the team actually works, not just talk about it
- A small, senior team where your technical calls carry real weight
- Flexible working setup and a clear path into engineering leadership
*If you'd rather be embedded in real delivery than sitting one layer removed from it — let’s talk.*
About Forward Deployed Engineering
Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.
Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.
Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.
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