Talently
Talently
Web3 Developer

Web3 Developer

Builds decentralized applications and smart contracts that operate on blockchain with security, efficiency, and transparency.

A Web3 Developer designs and implements decentralized applications (dApps) and smart contracts on blockchain networks such as Ethereum, Solana, or Polygon. Their work spans writing and auditing smart contracts through building the frontend that interacts with the blockchain and integrating with DeFi protocols, NFTs, and DAOs. Unlike traditional web development, the Web3 Developer works in an environment where deployed code is immutable, transactions are irreversible, and mistakes can cost millions. Security is not optional: it is the most critical requirement of the role. They collaborate with tokenomics designers, security auditors, and decentralized user communities.

SolidityEthereumHardhatethers.jsIPFSDeFi

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Main Responsibilities

  • •Design and implement smart contracts in Solidity with proven security patterns and gas optimization.
  • •Build dApp frontends with frameworks like React integrated with wallets (MetaMask, WalletConnect) via ethers.js or wagmi.
  • •Write exhaustive tests for smart contracts covering all possible paths including known attack vectors.
  • •Conduct security reviews of own contracts and identify vulnerabilities before mainnet deployment.
  • •Integrate DeFi protocols, token standards (ERC-20, ERC-721, ERC-1155), and external data oracles such as Chainlink.
  • •Manage the contract lifecycle: deployment, verification on block explorers, upgrades, and post-deployment monitoring.

Key Skills

Technical Skills

  • Advanced Solidity: contract design patterns, gas optimization, inline assembly, and deep knowledge of the EVM
  • Development and testing frameworks: Hardhat or Foundry for contract compilation, testing, deployment, and scripting
  • Web3 libraries: ethers.js or wagmi for frontend interaction with contracts and wallets
  • Token standards and protocols: ERC-20, ERC-721, ERC-1155, OpenZeppelin contracts, and DeFi protocols such as Uniswap and Aave
  • Contract security: deep knowledge of the most frequent attack vectors and their corresponding mitigations
  • Decentralized infrastructure: IPFS for storage, The Graph for event indexing, and Chainlink for oracles

Soft Skills

  • Offensive security mindset: think like an auditor or attacker before deploying to mainnet
  • Extreme testing rigor given that deployed contracts are immutable and errors are irreversible
  • Ability to design systems with correct economic incentives that cannot be exploited by malicious actors
  • Communication with both technical and non-technical communities about contract capabilities and limitations
  • Continuous learning in an ecosystem that evolves faster than any other in software development
  • Judgment to decide what logic belongs on-chain and what can stay off-chain to reduce cost and complexity

Real use cases

Context

DeFi protocols handle millions of dollars in total value locked. The correctness and security of their contracts is the difference between a successful protocol and an eight-figure exploit.

Real examples

  • ERC-20 token with staking, vesting, and reward distribution mechanics
  • Automated Market Maker (AMM) with liquidity pools and invariant-formula price calculation
  • Lending protocol with dynamic interest rates and collateral liquidation mechanisms
  • Yield aggregator that optimizes investment strategies across multiple DeFi protocols

Context

NFTs allow representing verifiable digital ownership. Their implementation requires correct standards, efficient metadata, and protection against reentrancy vulnerabilities in transfers.

Real examples

  • NFT collection with ERC-721 and IPFS-stored metadata generation
  • Marketplace with on-chain royalty support per EIP-2981
  • NFTs with dynamic attributes that change based on on-chain events or external oracle data
  • Mint mechanisms with allowlists, phase-based variable pricing, and bot minting prevention

Context

DAOs allow communities to make collective decisions transparently and without intermediaries. Their design determines whether governance is genuinely decentralized or susceptible to governance attacks.

Real examples

  • Voting system with token-weighted voting and timelock to execute approved proposals
  • Multisig governance with Gnosis Safe for DAO treasury management
  • Vote delegation allowing holders to delegate their voting power to representatives
  • Protection against flash loan attacks that could manipulate a vote in a single transaction

Context

Smart contracts are deterministic and cannot access external data on their own. Oracles are the bridge between the blockchain and the real world, with their own security considerations.

Real examples

  • Chainlink Price Feeds integration for real-time asset prices in DeFi protocols
  • Chainlink VRF usage for verifiable random number generation in games and NFTs
  • Integration with existing DeFi protocols like Uniswap or Aave from a custom contract
  • On-chain automation with Chainlink Automation to execute contract functions based on conditions

Context

Contracts are immutable by default, but long-lived projects need the ability to fix bugs or add functionality. Upgrade patterns are technically complex and carry their own security risks.

Real examples

  • Proxy patterns with OpenZeppelin Upgrades for upgradeable contracts with storage and logic separation
  • Upgrade process with timelock and multisig ensuring changes are reviewed and audited
  • Data migration from legacy contracts to new versions without loss of user state
  • Post-deployment monitoring with alert systems on anomalous contract behavior

Basic questions

Gas is the unit of measure for the computational cost of executing operations on the EVM. Each opcode has a gas cost that the user pays to the miner or validator. To optimize: use the correct data type sizes (uint256 is more efficient than uint8 in most cases due to EVM padding), pack variables from the same storage slot where possible (32 bytes per slot), prefer memory over storage for temporary variables (storage is 100-200x more expensive), avoid unbounded loops that could exceed the block gas limit, and use events for data that does not need to be read on-chain rather than storing it in storage.
Reentrancy occurs when a malicious external contract calls back into the original contract during a transfer's execution before the state is updated. The most famous attack is The DAO hack ($60M in 2016). Prevention: follow the Checks-Effects-Interactions pattern — verify conditions first, update the contract's state, then execute external calls. Never send ETH or call external contracts before updating state. Use OpenZeppelin's ReentrancyGuard's nonReentrant modifier for complex contracts. Prefer pull payments (the user withdraws their funds) over push payments (the contract sends funds) when possible.
call: executes another contract's code in the context of the called contract (its own storage). Used for normal external function calls. Returns success/failure and return data. delegatecall: executes another contract's code but in the calling contract's context (uses the caller's storage). The foundation of proxy patterns for upgradeable contracts. Dangerous if used incorrectly because the external contract can modify the caller's storage. staticcall: like call but reverts if the code attempts to modify state. Used for read-only calls that guarantee no side effects.
Events are low-cost records stored in transaction logs, not in contract storage. They are essential for dApps because: the frontend can subscribe to events to react to contract changes in real time, indexing services like The Graph use them to build queryable databases of the contract's historical state, and they are the most economical way to record information that does not need to be read by other contracts. Indexed event parameters (marked with indexed) allow efficient log filtering. Not emitting events on important operations is an anti-pattern that makes the dApp difficult to integrate and audit.
Frontrunning occurs when an actor (typically an MEV bot) observes a pending transaction in the mempool and sends their own transaction with higher gas to execute first. In an auction: a bot can see the winning bid and submit a slightly higher bid before it is included in the block. In a DEX: a bot can see a large swap that will move the price, buy before the swap, and sell after (sandwich attack). Mitigations: commit-reveal scheme for auctions (the user first commits a hash of their bid, then reveals it when the commit period closes), slippage protection in DEX (the transaction reverts if the price moves more than an accepted percentage), and use of MEV-aware protocols like Flashbots.
Blockchain nodes must be able to independently verify the result of every transaction to reach consensus. If a contract could call an external API, different nodes would potentially get different responses, making consensus impossible. The oracle problem is the challenge of introducing real-world data into the blockchain in a verifiable and manipulation-resistant way. Chainlink solves this with a decentralized network of oracles that aggregate data from multiple sources and provide cryptographic proofs of data integrity. The oracle risk does not disappear: if the oracle is manipulated or fails, the contract uses incorrect data. This is why major DeFi protocols use multiple price sources with anti-manipulation mechanisms such as TWAPs (Time-Weighted Average Prices).
The proxy pattern separates contract storage (in the proxy) from logic (in the implementation). The user interacts with the proxy, which uses delegatecall to execute the implementation's logic in its own storage context. To upgrade, a new implementation is deployed and the pointer in the proxy is updated. Critical risks: storage collision (if the new implementation uses the same storage slots with different types, it can corrupt data), initialization issues (constructors do not run on upgrades — initializer functions are used and must be protected with modifiers), and centralization of upgrade control (whoever can upgrade the contract has total power over it). OpenZeppelin UUPS and Transparent Proxy are the most audited and widely used implementations.
ERC-20: fungible tokens where all units are identical and interchangeable. For currencies, governance tokens, utility tokens. ERC-721: non-fungible tokens where each token has a unique ID and can have distinct attributes. For art NFTs, collectibles, unique asset representation. ERC-1155: multi-token standard supporting both fungibles and non-fungibles in the same contract with batch transfers. For games that have currencies (fungible) and unique items (non-fungible), or for collections where some tokens are scarce (non-fungible) and others are common (semi-fungible). ERC-1155 is more gas-efficient for multiple transfers and reduces the number of contracts needed.

Technical questions

The accumulated rewards-per-token algorithm is the standard for reward distribution without iteration. Maintain a global rewardPerTokenStored variable that accumulates rewards per token over time. For each user, store the rewardPerTokenPaid at the time of their last claim or stake. A user's pending rewards are (rewardPerTokenStored - rewardPerTokenPaid[user]) × balanceOf[user] + rewards[user]. Update rewardPerTokenStored on every stake, unstake, or claim operation using the time elapsed since the last update. This pattern — implemented in Synthetix Staking Rewards — is O(1) regardless of the number of stakers because it never iterates over all users.
Tests must cover: mathematical correctness of price calculations using the x*y=k invariant, verifying the formulas produce correct results with fixed-point precision. Reentrancy in swap and addLiquidity functions using an attack contract that attempts to re-enter during execution. Price manipulation: verify that price cannot be manipulated in a single block in a way that affects other operations in the same block. Slippage protection: verify that swaps revert if slippage exceeds the specified maximum. Flash loan attacks: simulate a flash loan that takes pool liquidity, executes a manipulation, and returns the liquidity, verifying the contract is resistant. Invariant testing with Foundry using fuzzing on critical functions to discover unexpected states.
Flash loan attacks on governance borrow governance tokens, vote on a proposal, and return them in the same transaction. The standard mitigation is to use balance snapshots at a block prior to the voting period: voting power is calculated at block N (the snapshot block) and voting starts from block N+delay. Tokens acquired or borrowed after the snapshot have no voting power on that proposal. Implementation with OpenZeppelin Governor: the governance token must implement ERC20Votes, which records balance checkpoints per block. The Governor uses getVotes(account, blockNumber) with the snapshot blockNumber to calculate voting power. The additional timelock between proposal approval and execution gives the community time to react to malicious proposals.
Arrays in storage are expensive: each element read and write is an SLOAD/SSTORE operation (100 and 20,000 gas respectively). Strategies: load the full array into memory at the start of the function and operate on the memory copy, writing back to storage only at the end if there are changes. Use mappings instead of arrays when access is by key and iteration is not needed: mappings have O(1) cost instead of O(n). For arrays that must be iterated in the contract, enforce a maximum length so gas never exceeds the block gas limit. For processing unbounded arrays, use the batch processing pattern where the caller pays the gas for each batch.
Implement following the Checks-Effects-Interactions pattern. First verify (checks): require(balances[msg.sender] >= amount, error). Then update state (effects): balances[msg.sender] -= amount (using Solidity 0.8+ which has native overflow protection, or SafeMath in earlier versions). Finally execute the transfer (interactions): (bool success, ) = msg.sender.call{value: amount}(''); require(success). OpenZeppelin's nonReentrant modifier as a second line of defense. With Solidity 0.8+, overflows and underflows revert automatically without needing SafeMath. Use custom errors instead of require strings to reduce the gas cost of reverts.
Create a subgraph with the entity schema (the objects to be queried: Token, Transfer, User) defined in schema.graphql. In subgraph.yaml, define the data sources: which contract to index, from which block, and which events to listen to with their mappings. Mappings are AssemblyScript functions that execute on each event and create or update entities in the subgraph store. For example, on an ERC-20 Transfer event, the mapping creates or updates the Token entity with the new supply, and updates the sender and recipient wallet balances. The subgraph is deployed to The Graph Network or a self-hosted node. The frontend queries historical contract state via GraphQL without depending on a centralized backend.
Use wagmi or RainbowKit, which abstract multi-chain management with declarative configuration. Define the list of supported chains with their RPC endpoints, block explorers, and contract addresses. The frontend detects the user's wallet active chain and displays the corresponding state. For contract addresses, maintain a configuration object indexed by chainId that the frontend queries based on the active chain. Contracts on different networks do not share state, so the frontend must manage the context of which network is active and what data to display. Implement an abstraction layer that wraps contract calls so the rest of the frontend does not need to manage the active chain directly.
The audit process has multiple layers. Automated static analysis: Slither detects known vulnerabilities (reentrancy, integer overflow, unchecked return values, tx.origin usage) in seconds. Mythril and Echidna for deeper analysis with fuzzing. Systematic manual review: read the contract line by line using the OWASP Smart Contract Top 10 and the SWC Registry as a checklist. Review specifically: access to privileged functions, ETH and token handling, interactions with external contracts, timestamp and block number manipulability, and mathematical correctness of financial calculations. Invariant testing with Foundry: define properties that must always be true and use fuzzing to attempt to violate them. For contracts handling significant value, an independent external audit is mandatory before mainnet.

Advanced questions

Least privilege principle between contracts: each contract has access only to the contracts it needs and only to the functions it needs. Separate responsibilities into distinct contracts: the protocol logic contract separated from the fund storage contract (vault). Explicit interfaces between contracts so dependencies are transparent. The vault contract only accepts calls from the logic contract — never directly from users. Pausability with differentiated roles: an emergency pause role that can stop the protocol without needing the full timelock when an exploit is in progress. User funds must never pass through more contracts than strictly necessary: each additional hop is an attack surface. The governance contract's timelock ensures protocol changes have a public review period before execution.
A death spiral occurs when a drop in governance token price reduces liquidity provider incentives, which reduces liquidity, which increases slippage, which reduces protocol usage, which reduces revenue, which reduces the token price. Design to avoid it: protocol revenue must be independent of governance token price (usage fees that exist even if the token is worth zero). Token emissions as incentives must be finite and decreasing — not infinite. Protocol liquidity must not depend primarily on token emissions: if liquidity only exists due to incentives, it disappears when incentives end. Token burning mechanisms that reduce supply with growing usage can create organic price pressure. Mathematically model the system's equilibrium before launch to identify collapse scenarios.
Cross-chain bridges have a history of exploits (Ronin, Wormhole, Nomad). The safest current architecture is to use audited cross-chain messaging protocols (LayerZero, Axelar, Wormhole v2 with its guardian model) rather than building a custom bridge. The contract on the source chain sends a message to the messaging protocol specifying the action to execute on the destination chain. The contract on the destination chain verifies the message's authenticity and executes the action. The greatest complexity is state management on failure: if the message arrives but the transaction fails on the destination chain, the source chain state has already been modified. Design for eventual consistency with retry and refund mechanisms if the operation cannot be completed.
TVL is not a security indicator. Evaluation requires: reviewing the protocol's audit reports (who audited, when, what findings were identified, and how each was resolved). Time in production without incidents: the safest protocols have at least 12-18 months on mainnet at the current TVL without exploits. Review the code directly on Etherscan or the repository: are contracts verified? Do they match what the documentation says? Evaluate control centralization: is there a multisig with a timelock managing upgrades, or can an EOA (Externally Owned Account) without restrictions pause or drain the protocol? Review the incident history and how it was handled. For the integration, assume the external protocol may be paused or compromised and design your own contract to handle that scenario gracefully.
DeFi exploits happen in seconds. The response process must be pre-designed — not improvised. Preventive design: the contract must have an emergency pause function accessible by a fast-response multisig (3-of-5 signers with the core devs) without a timelock, separate from the normal governance process which does have a timelock. Upon detecting the exploit (automated anomalous transaction monitoring, community Discord alerts): verify the exploit is real, pause the contract if there is a pause function, and contact exchanges and bridges to flag the attacker's transactions if they still hold the funds. Communicate to the community in real time with available information. Post-exploit: complete forensic analysis, responsible disclosure of the exploit, remediation plan, and if possible, negotiation with the attacker (many exploiters return funds in exchange for a bounty). Independent audit before resuming the protocol.
Blockchain transparency is a feature — not just a problem — but there are use cases where privacy is a legitimate requirement. Technical approaches: Zero-Knowledge Proofs (ZKPs) allow proving knowledge of information without revealing it (that you have sufficient balance for a payment without revealing the balance). Tornado Cash was the best-known example of ETH privacy using ZKPs, with significant regulatory implications. For enterprise applications, permissioned networks like Hyperledger Fabric or Quorum allow selective transaction visibility. For user metadata (which wallet belongs to which person), wallet separation and the use of stealth addresses add privacy without protocol changes. The designer must evaluate what data genuinely needs to be public on-chain and what can stay off-chain with only its hash or commitment stored on-chain.

Common interview mistakes

A Web3 Developer who cannot discuss reentrancy, flash loan attacks, price manipulation, frontrunning, and unauthorized access to privileged functions demonstrates developing contracts without the security mindset the domain demands. Auditors and security teams interviewing for these roles expect the candidate to think about adversaries from the design stage.
Contracts deployed to mainnet are immutable and handle real funds. A candidate who describes their development process without mentioning testing with Hardhat/Foundry, fuzzing with Echidna, static analysis with Slither, and an external audit before mainnet demonstrates applying the same rigor as traditional web development to a domain where a single bug can cost millions.
Putting everything on the blockchain because the project is Web3 is a design error that produces expensive, slow contracts with unnecessarily complex logic. A good Web3 Developer can articulate what requires blockchain guarantees (value transfers, ownership, voting) and what can stay off-chain (NFT metadata on IPFS, order-matching logic on a server) — reducing cost and complexity.
Not all problems require a blockchain solution. A candidate who proposes blockchain for use cases where a centralized database would be more efficient, cheaper, and provide better guarantees demonstrates hype-driven thinking rather than engineering judgment. Blockchain has real costs (latency, gas cost, complexity) that are only justified when its decentralization guarantees are genuinely necessary.
Security tokens, mixing protocols, interest-bearing lending systems, and other Web3 use cases have significant regulatory implications that vary by jurisdiction. A Web3 Developer who completely ignores these implications may build something technically correct but produce a product that faces legal challenges that destroy the project.
Users pay gas for every transaction. A contract with expensive operations produces a poor user experience that reduces adoption. A Web3 Developer who cannot discuss the most expensive EVM operations, storage packing strategies, or the impact of gas on contract architecture decisions demonstrates not having developed contracts with real users.