How to Evaluate RISC-V and AI Chip Talent for Your Dubai Engineering Team in 7 Steps

The AI chip talent market has shifted. With Qualcomm's $14 billion acquisition of Tenstorrent and Modular, RISC-V architecture and open AI compilers have moved from niche research topics to mainstream hiring requirements. For Dubai engineering leaders, the challenge is no longer whether to hire chip talent — it is how to evaluate candidates in a domain where most hiring managers have zero assessment experience.

This guide provides a practical 7-step framework for evaluating RISC-V and AI chip engineering candidates, specifically designed for UAE employers who are building these capabilities for the first time. Each step includes the technical signals to look for, the red flags to avoid, and the Dubai-specific considerations that make chip talent hiring in the Gulf different from Silicon Valley or Taipei.

The framework works across all three chip talent categories that matter for UAE AI infrastructure: RISC-V chip designers, AI compiler engineers (Mojo, MLIR, LLVM), and hardware-software integration architects. Adapt the technical depth to the role level, but follow all seven steps for every hire.

Step 1: Test architecture literacy before touching a resume

The single biggest mistake Dubai employers make when hiring chip engineers is evaluating resumes before defining what architecture literacy means for their specific use case. A RISC-V engineer who designed custom extensions for edge inference at SiFive has a fundamentally different skill profile from one who built data center accelerators at Tenstorrent. Both are valuable. Neither is interchangeable.

Before you review a single CV, define your Architecture Literacy Checklist by answering these questions:

• What AI workloads will run on this hardware? Inference-only (fraud detection at Emirates NBD, predictive maintenance at ADNOC) requires different architecture knowledge than training + inference (G42 Stargate-scale compute).
• What ISA variants matter? RV64GC for general-purpose compute? Custom vector extensions (RVV 1.0) for AI acceleration? Matrix extensions for tensor operations? Your checklist should specify which RISC-V extensions the candidate must understand.
• What level of silicon experience is required? RTL design and simulation? FPGA prototyping? Full tape-out to GDS-II? Each level represents a different depth of expertise and dramatically affects your candidate pool size.
• What compiler/software stack integration is needed? If your team will use Modular's Mojo and MAX Platform, candidates need to understand how hardware design decisions affect compiler optimization. If you are running CUDA-to-Mojo migration, the candidate needs cross-stack knowledge.

Create a scoring rubric with 10 architecture literacy criteria weighted by importance to your specific UAE deployment. Use this rubric to screen every candidate consistently, eliminating the bias that comes from being impressed by a big-name employer on a resume without understanding whether the work is relevant to your needs.

Step 2: Conduct a structured portfolio and contribution review

Chip engineering portfolios look nothing like software portfolios. You will not find polished GitHub repos with thousands of stars. Instead, look for these signals of genuine chip engineering expertise:

Published silicon. Has the candidate contributed to a chip that was manufactured and deployed? Even a contribution to a single block (memory controller, interconnect, custom accelerator unit) on a shipped chip demonstrates the ability to work within the constraints of real silicon — timing closure, power budgets, manufacturing yield. Ask for the chip name, the process node, and the candidate's specific contribution. In the UAE context, published silicon for AI workloads (inference accelerators, NPUs, custom DSP blocks) is especially valuable.

RISC-V open-source contributions. The RISC-V ecosystem is built on open collaboration. Candidates with contributions to projects like BOOM (Berkeley Out-of-Order Machine), Rocket Chip, CVA6, or OpenTitan demonstrate both technical depth and the collaborative mindset needed for UAE teams that are building from scratch. Check their commits, not just their membership in repositories.

Conference papers and patents. Chip engineers publish at venues like ISSCC (International Solid-State Circuits Conference), DAC (Design Automation Conference), MICRO, and ISCA. A paper at any of these venues indicates peer-reviewed technical depth. Patents on AI accelerator architectures, memory hierarchy designs, or custom RISC-V extensions are equally strong signals. For Dubai employers, candidates with publications on energy-efficient AI computing or edge inference optimization align well with UAE data center priorities in extreme thermal environments.

Red flags in portfolios:

• Claiming credit for an entire chip when they worked on a single verification block — ask for specificity
• No measurable outcomes (PPA improvements, area reduction, power savings) — real chip engineers quantify everything
• Only academic or FPGA experience with no path to production silicon — acceptable for mid-level hires but insufficient for senior roles leading your Dubai chip initiative
• Listing "RISC-V" as a skill but unable to explain the difference between RV32I and RV64GC extensions

Step 3: Design a RISC-V RTL coding challenge calibrated to UAE workloads

The technical assessment is where most Dubai employers fail because they either use generic software engineering challenges (irrelevant to chip design) or they borrow Nvidia/Intel interview questions that test knowledge of those companies' proprietary architectures rather than transferable design skills. Here is a three-tier challenge framework calibrated to UAE AI workloads:

Tier 1: Live coding (45 minutes, all levels). Ask the candidate to implement a simple RISC-V pipeline stage in SystemVerilog or Chisel. Specifically: design a 5-stage in-order pipeline with a custom RISC-V extension for a fused multiply-accumulate (FMA) operation used in neural network inference. The FMA instruction is the atomic operation of AI compute, and implementing it as a custom extension tests ISA understanding, pipeline hazard management, and awareness of AI workload requirements simultaneously.

What to evaluate: Does the candidate correctly handle data hazards (forwarding vs stalling)? Do they consider the timing implications of the FMA unit? Can they explain how this custom extension would be exposed to the compiler through RISC-V's extension mechanism? Senior candidates should spontaneously discuss power gating the FMA unit when it is not in use — a critical consideration for UAE data centers managing thermal loads.

Tier 2: Take-home design (4–6 hours, senior+ levels). Provide the candidate with a specification for a small AI inference accelerator block: a tensor processing unit that takes 8x8 INT8 matrix inputs and produces 8x8 INT32 outputs using a systolic array architecture. The candidate must deliver RTL code, a testbench, and a brief architecture document explaining their design decisions. For UAE relevance, specify that the design must optimize for inference latency (not training throughput) and include a power management interface.

Tier 3: Architecture presentation (60 minutes, principal/staff levels). Give the candidate 48 hours to prepare a 30-minute presentation answering this question: "Design a RISC-V-based AI inference chip optimized for real-time fraud detection at a Dubai financial institution processing 50,000 transactions per second. The chip must operate within a 75W TDP in an air-cooled UAE data center where ambient temperature reaches 45°C." Follow with 30 minutes of Q&A. This tests architecture judgment, thermal awareness (critical for UAE), and the ability to translate business requirements into silicon specifications.

Step 4: Assess compiler and software stack integration skills

The lesson from Nvidia's dominance is clear: silicon without a software ecosystem is useless. CUDA is the reason Nvidia wins, not raw GPU performance. For RISC-V AI chips to succeed, they need compiler engineers who can make the hardware accessible to AI developers. When evaluating candidates for your Dubai team, assess their ability to bridge hardware and software.

For AI compiler engineer candidates (Mojo/MLIR/LLVM specialists), test these skills:

• MLIR dialect design. Can the candidate design a custom MLIR dialect that maps neural network operations to your RISC-V chip's custom instructions? Give them a simple AI operation (e.g., a 2D convolution with fused ReLU activation) and ask them to sketch the MLIR lowering pipeline from a high-level TensorFlow/PyTorch graph to RISC-V assembly with custom vector extensions.
• Mojo proficiency. If your team will use Modular's stack, test the candidate's ability to write Mojo code that achieves near-hardware-optimal performance. A practical exercise: implement a matrix multiplication kernel in Mojo that uses SIMD intrinsics and compare its performance to an equivalent CUDA kernel. The candidate should articulate why Mojo's ownership model and compile-time metaprogramming enable performance that Python cannot achieve.
• Cross-hardware optimization. The unique value of Modular's MAX Platform is hardware-agnostic optimization. Ask the candidate to explain how MAX compiles the same AI model for three different targets: an Nvidia H100, a Tenstorrent Wormhole, and a Qualcomm Cloud AI 100. What optimization passes differ? Where are the performance cliffs? This question reveals whether the candidate truly understands hardware-software co-optimization or is just a single-platform specialist.

For hardware-software integration architects, the critical assessment is the ability to make architecture decisions that benefit both silicon and software teams. Present a design trade-off: "You have a fixed transistor budget. Do you add more RISC-V vector lanes (benefiting compute-bound workloads) or enlarge the on-chip SRAM (benefiting memory-bound workloads)? Your AI compiler team says memory. Your chip design team says compute. How do you decide?" The best candidates will ask about the target workload mix, model the performance impact of each choice, and propose a configurable solution that serves both needs.

Step 5: Evaluate UAE sovereign AI context fit

This step is unique to Gulf employers and is often the step that separates candidates who will thrive in Dubai from those who will struggle and leave within 12 months. RISC-V and AI chip engineering in the UAE is not the same as at Tenstorrent in Toronto or Modular in San Francisco. The constraints, incentives, and mission are different, and the best candidates understand and embrace those differences.

Key evaluation questions for this step:

• "Why does sovereign AI compute matter, and how does RISC-V contribute to it?" The candidate should articulate that sovereign AI means a nation's ability to run AI workloads without dependency on foreign vendors for hardware IP, compiler toolchains, or cloud infrastructure. RISC-V's open ISA eliminates the hardware IP dependency. The best candidates will connect this to the UAE AI Strategy 2031 and explain how RISC-V enables the UAE to design custom AI accelerators optimized for national priorities (oil and gas, finance, logistics, smart city) without Arm or Intel licensing constraints.
• "How would you design an AI chip for a data center where ambient temperature exceeds 45°C?" This is a practical question that reveals whether the candidate has thought about UAE-specific operating conditions. Desert data centers face unique thermal challenges that affect chip TDP budgets, cooling infrastructure costs, and reliability. Candidates who immediately discuss dark silicon strategies, dynamic voltage and frequency scaling (DVFS), and workload-aware power management demonstrate readiness for UAE deployment.
• "What is your understanding of the UAE's position in the global semiconductor supply chain?" Strong candidates will discuss GlobalFoundries' fabrication facilities in relation to the UAE (GF was spun out of AMD and has Middle East investment connections), the role of TSMC and Samsung foundry access for RISC-V chips, and the geopolitical dynamics that make hardware independence strategically important for Gulf states. Weak candidates will not have thought about supply chain at all.

This step should take 30–45 minutes and can be conducted by a senior engineering leader or CTO. It is a conversation, not a test. You are evaluating intellectual curiosity, strategic thinking, and genuine motivation to build sovereign AI infrastructure in the UAE — not memorized facts about the region.

Step 6: Conduct domain-specific reference checks

Standard reference checks ("Was this person a good employee?") are useless for chip engineering hires. The domain is so specialized that only people who have worked on similar projects can evaluate a candidate's contribution accurately. Here is how to conduct references that actually reveal signal:

Ask for references from within the candidate's specific project. Not their manager (who may have managed 30 engineers and cannot speak to individual technical contributions), but a peer engineer or technical lead who worked on the same block, the same tape-out, or the same compiler pass. These references can validate whether the candidate actually designed the RTL they claim, actually wrote the compiler optimization they describe, or actually led the architecture decisions they present.

Ask technical questions in the reference call. "Can you describe a specific design decision that [candidate] made on [project] and how it affected the chip's PPA (power, performance, area)?" "When a timing closure issue arose, what was [candidate]'s approach to resolving it?" "How does [candidate] handle disagreements with the verification team?" These questions reveal whether the candidate is a genuine technical contributor or a project manager who claims engineering credit.

Cross-reference with open-source contributions. If the candidate claims RISC-V expertise, check their GitHub, GitLab, or Bitbucket activity for contributions to RISC-V cores, toolchains, or verification frameworks. The RISC-V community is small enough that genuine contributors are known. If a candidate claims significant RISC-V experience but has zero public contributions and no references from within the RISC-V ecosystem, treat this as a yellow flag.

For Dubai-specific validation: If possible, include a reference check with someone who has worked in a Middle East or Gulf technology organization. Candidates who have successfully relocated to or worked in similar environments (Singapore, Taiwan semiconductor hubs with intense work cultures, or Gulf tech companies) are more likely to thrive in Dubai than those whose entire career has been in the relaxed pace of a Bay Area research lab.

Step 7: Design the offer with Golden Visa, tax advantage, and retention in mind

The final step is where Dubai employers have their greatest structural advantage — and where most waste it by presenting generic offer letters. RISC-V and AI chip engineers are evaluating opportunities across San Francisco, Toronto, Taipei, Bangalore, Munich, and now Dubai. Your offer must make the UAE's unique value proposition unmistakably clear.

Lead with net take-home, not gross compensation. A RISC-V engineer earning AED 80,000/month in Dubai takes home AED 80,000 due to zero income tax. The same engineer earning the equivalent $22,000/month in San Francisco takes home approximately $13,200 after federal (37%), California state (13.3%), and city taxes. That is a 60% higher take-home in Dubai at the same gross compensation. Present this math explicitly in every offer letter. Most candidates from North America and Europe have never done the calculation and are shocked by the delta.

Include Golden Visa processing as a day-one benefit. The UAE Golden Visa grants 10-year residency to qualifying technology professionals. For chip engineers, this is transformative: it means they can build a career in Dubai without the visa uncertainty that plagues expatriates in every other Gulf country. Process the Golden Visa application immediately upon acceptance, not after a probation period. The certainty of 10-year residency is one of Dubai's most powerful hiring tools.

Build retention into the compensation structure. Chip engineering projects have multi-year timelines. A RISC-V chip design cycle from RTL to tape-out is 18–24 months minimum. Structure compensation with cliff bonuses at 18 and 36 months, matching the project milestones. For example: base salary of AED 90,000/month + AED 200,000 cliff bonus at first tape-out milestone (18 months) + AED 400,000 cliff bonus at production silicon qualification (36 months). This structure aligns the engineer's incentives with your chip development timeline and makes it economically painful to leave mid-project.

Offer sovereign compute access. For top-tier chip architects, access to UAE sovereign AI infrastructure (G42 Stargate compute, ADNOC AI platform, Dubai Smart City data) is a unique technical incentive that no Bay Area employer can match. These architects want to see their designs deployed at national scale, not just sell chips to hyperscalers. Frame the role as "build the silicon that powers an entire nation's AI strategy" — a mission statement that resonates with engineers who are motivated by impact, not just compensation.

For a broader framework on structuring AI engineering offers in the UAE, refer to our guide on building an AI engineer assessment framework for Dubai startups.

FAQ — Evaluating RISC-V and AI chip talent in Dubai

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