Forward Deployed Engineer (FDE)

Who we are:

devx Labs is an AI-native consulting firm that fundamentally reimagines business operations around AI capabilities. We don’t just implement AI tools - we transform how enterprises operate through first-principles thinking and outcome-driven execution.

About the Role:

• As a Forward Deployed Engineer, you are embedded inside the client's world - their data, their stack, their constraints - not building in isolation and handing off a spec. You sit with the client team, watch how they actually work, and ship something they can use that week.
• This is not an architecture role. It's the role that makes the first version real, proves the value fast, and hands off a system the AI Engineering team can harden and scale.
• You'll move across engagements - wherever devx needs someone who can parachute in, understand a client's system in days, and build the thing that unblocks the engagement.

Embedded Delivery (50%)

• Live in the client's environment: Work from the client's data, APIs, and systems directly - not a sanitized dev sandbox. Get comfortable with real-world mess (undocumented APIs, legacy data, conflicting requirements).
• Ship the first working version fast: Build functional prototypes and MVPs in days, not sprints - using AI-assisted development (Claude Code) to move at 2–3x normal velocity.
• Unblock the engagement: Identify the one thing standing between the client and value, and build that first - even if it's not the "complete" solution.
• Iterate live with the client: Sit in on client working sessions, take feedback in real time, and reship within the same day where possible.

Technical Translation & Trust (30%)

• Be the technical presence in the room: Represent devx's engineering credibility directly with client stakeholders — engineers, ops teams, sometimes leadership.
• Surface hidden problems early: Because you're inside their systems, you'll often find the real blocker before it becomes a delivery risk. Flag it fast to Practice Leaders and Outcome Managers.
• Translate constantly: Convert client-speak ("our checkout keeps breaking") into technical scope, and technical tradeoffs back into terms the client can decide on.

Handoff & Scale (20%)

• Package what you built: Document the system, the decisions, and the gotchas so the AI Engineer / AI-Native Engineer team can take it from working prototype to production-grade.
• Feed the playbook: Every engagement teaches devx something reusable — patterns, accelerators, integration quirks. Capture it.
• Know when to stay, know when to leave: Part of the job is judgment — recognising when an engagement needs you to stay embedded longer vs. when it's ready to transition to the standing delivery team.

Mindset

• Comfortable with ambiguity and messy, undocumented client environments — you don't wait for a clean spec.
• Bias to shipping something real over presenting something polished.
• Enjoys being client-facing and technical in the same day — not purely back-office engineering.

Technical Skills

• Strong hands-on full-stack ability: TypeScript, Next.js, Postgres, and comfort picking up whatever the client's stack already is.
• Gemini Enterprise experience is a must: devx labs is a Gemini Enterprise Partner, and FDE engagements frequently involve deploying and configuring Gemini Enterprise inside client environments — hands-on experience with it (or the ability to demonstrate deep Google Cloud AI stack fluency and ramp fast) is a hard requirement.
• Working knowledge of agentic AI systems — building and wiring up agents against real client data and APIs, not just calling an LLM endpoint.
• Can go from "here's an API and some CSVs" to a working integration without hand-holding.
• Proficiency with AI-assisted development tools (Claude Code) as a default way of working, not an occasional aid.

Client & Leadership

• Can hold a technical conversation directly with a client engineer or ops lead without a consultant translating for you.
• Comfortable presenting a rough, working demo to a client and taking live feedback — polish comes later.
• Clear, concise documentation habits — what you build has to survive after you leave.

Experience

• 3–7 years of software engineering, with at least one stretch of direct client-facing or on-site delivery work (consulting, implementation, solutions engineering, or startup founding-engineer experience).
• Track record of shipping working software under real time pressure, not just in controlled sprints.
• Comfortable with travel and time away from home base for engagements

• AI tool credits and freedom to experiment with modern approaches.
• Performance-based appraisal at 6 months + annual appraisal cycle.
• Competitive pay with a structured CTC breakup.
• Work with clients across industries and domains.
• Hybrid model with work-from-home support and flexible working hours.
• No-cap leave policy — take time off responsibly, no fixed limits.
• Health insurance with spouse and kids coverage included.
• Yearly outings, and an open environment for innovation.