At Franklin Templeton, we’re advancing our industry forward by developing new and innovative ways to help our clients achieve their investment goals. Our dynamic firm spans asset management, wealth management, and fintech, offering many ways to help investors make progress toward their goals. Our talented teams working around the globe bring expertise that’s both broad and unique. From our welcoming, inclusive, and flexible culture to our global and diverse business, we provide opportunities to help you reach your potential while helping our clients reach theirs.

About

The Department

The Digital Assets Technology group builds blockchain-based infrastructure shaping the future of asset management and capital markets. The team consists of experienced engineers who collaborate closely with product and design partners to research, experiment, and deliver secure solutions that tokenize securities across multiple blockchain platforms. We operate at the intersection of institutional finance and emerging technology, delivering production-grade systems that serve real-world regulated assets.

Role Overview

We are looking for a Blockchain Development Engineer who combines deep smart contract expertise with fluency in AI‑assisted development practices. This is not a role where AI tools are optional or aspirational — we expect you to use AI coding assistants, LLM‑driven testing and review workflows, and generative AI tooling as core parts of your daily engineering process. Your blockchain fundamentals must be strong enough that you can critically evaluate and improve AI‑generated output in a domain where deployed bugs are irreversible and security is non‑negotiable.

How

You Will Add Value AI‑Augmented Development

• Use AI coding assistants (Codex, Cursor, Claude Code, or equivalent) as a primary development accelerator across the full lifecycle — prototyping, implementation, testing, and documentation
• Apply LLM‑driven workflows for automated code review, test generation, security analysis, and architectural reasoning on smart contract codebases
• Critically evaluate AI‑generated Solidity and Rust code for security vulnerabilities, gas optimization issues, and compliance gaps — recognizing that AI output in smart contract contexts requires expert human judgment
• Identify and implement opportunities to integrate AI tooling into team workflows, CI/CD pipelines, and quality assurance processes
• Stay current with rapidly evolving AI‑assisted development tools and techniques, evaluating new capabilities for team adoption

Blockchain Engineering

• Design, develop, and deploy smart contracts across EVM‑compatible networks and Stellar, with a focus on security, efficiency, and regulatory compliance
• Build and maintain multi‑chain deployment infrastructure and tooling to support the department’s blockchain footprint
• Test and audit smart contracts using formal verification tools and security frameworks (Foundry, Slither, or equivalent)
• Maintain and upgrade deployed contracts with backward compatibility, migration strategies, and rigorous change management
• Collaborate with engineers, product partners, and designers to translate business requirements into robust on‑chain solutions

What Will Help You Be Successful

• 5+ years of software engineering experience on mission‑critical or production‑grade systems
• 3+ years of hands‑on blockchain development and smart contract deployment
• Demonstrated, ongoing use of AI‑assisted development tools (Copilot, Cursor, Claude Code, or similar) as a core part of the engineering workflow — not experimental or occasional
• Bachelor’s degree in Computer Science, Engineering, or equivalent professional experience

Required Technical Skills

• Solidity:

Production‑level proficiency; experience writing, deploying, and auditing smart contracts on EVM‑compatible chains (Ethereum, Avalanche, Polygon, Arbitrum, or similar)

• Stellar:

Working knowledge of the Stellar network is desired.

• Type Script/JavaScript:

Proficiency in full‑stack development with Node.js and modern frameworks

• AI/LLM Tooling:

Hands‑on experience using AI assistants for code generation, review, debugging, and test authoring; ability to craft effective prompts and…