Lead AI Software Engineer

J Harlan Group • New York, NY

6h • Hybrid

About The Position

J Harlan Group is currently conducting a search for a Lead AI Software Engineer to join the firm's AI Engineering team at a prominent global Investment Manager. This role offers the opportunity to collaborate with talented engineers, product owners, business partners, senior stakeholders, and technology leaders building high-impact AI products with leverage across the firm. As a Lead Software Engineer on T. Rowe Price Labs' AI Engineering team, you will lead the architecture, design, and delivery of complex production-grade AI agents and intelligent systems. You will lead the incubation of new AI products, drive experimentation with emerging technologies and innovative ideas, and partner with business-aligned technology teams to enable broader adoption at enterprise scale. This is a hands-on technical leadership role for an experienced engineer with deep software and AI engineering expertise who enjoys solving complex and ambiguous problems, mentoring engineers, and shaping technical direction. You will guide the development of reusable AI capabilities, influence engineering standards across teams, and help define the future of AI engineering across the firm. What makes this opportunity particularly compelling is the combination of deep software engineering, production AI, architecture, and technical leadership. The team is building sophisticated systems incorporating AI agents, agent orchestration, tool and function calling, retrieval-based systems, prompt and context engineering, evaluation frameworks, observability, guardrails, failure handling, and modern cloud-native infrastructure. The position is not focused on AI research or training foundation models. Instead, it focuses on architecting, building, productionizing, and scaling modern AI applications and intelligent systems that are reliable, measurable, secure, cost-effective, and capable of operating within a sophisticated enterprise environment. The firm's AI Labs focuses on building its next generation of data and AI capabilities and developing high-impact technology solutions that can ultimately be scaled across the organization.

Requirements

• BS or MS in Computer Science or a related technical field, or equivalent practical experience, with 8+ years of progressive software engineering experience.
• Extensive hands-on software engineering experience in object-oriented languages such as Python, Java, or JavaScript/TypeScript, including experience leading technical delivery across teams or major initiatives.
• Deep hands-on experience designing and delivering AI-enabled systems, intelligent workflows, or agentic applications in production or near-production environments.
• Strong expertise in modern AI engineering patterns such as agent orchestration, tool/function calling, retrieval-based systems, prompt and context engineering, evaluation, observability, guardrails, and failure handling.
• Demonstrated ability to architect production AI systems and make informed trade-offs across model capability, quality, latency, cost, reliability, security, and maintainability.
• Extensive experience architecting and delivering cloud-native solutions using AWS or equivalent, containerized microservices, APIs, and modern software delivery practices.
• Strong understanding of evaluation and testing strategies for AI systems, including approaches for measuring and improving non-deterministic system behavior.
• Exceptional analytical, problem-solving, architecture, and system-design skills, with demonstrated ability to lead engineers through complex and ambiguous technical challenges.
• Demonstrated commitment to engineering excellence through setting and upholding standards for automated testing, code reviews, observability, security, and continuous delivery.
• Strong communication and influence skills, with the ability to shape technical direction across engineering, product, business, and senior stakeholders.
• Demonstrated experience mentoring engineers and raising technical capability across teams.
• Passion for staying current with the rapidly evolving AI landscape and the judgment to distinguish promising technologies from short-lived trends.

Nice To Haves

• Experience establishing engineering standards or technical direction across multiple teams.
• Understanding of financial markets, asset management, or financial instruments.

Responsibilities

• Lead the architecture, design, development, deployment, and evolution of complex production-grade AI agents and intelligent systems.
• Set technical direction for AI solutions, making informed trade-offs across models, orchestration patterns, retrieval, tools, data, infrastructure, latency, cost, security, reliability, and long-term maintainability.
• Lead teams through ambiguous and technically complex AI problems, from experimentation and architecture through production adoption and scale.
• Define and evolve engineering standards for production AI, including evaluation, testing, observability, guardrails, failure handling, security, and responsible deployment.
• Guide the development of reusable AI capabilities and shared platform components across areas such as agent orchestration, tool use, retrieval-based systems, evaluation frameworks, observability, and guardrails.
• Evaluate emerging models, frameworks, tools, and AI engineering approaches and provide technical direction on when and how they should be adopted.
• Provide hands-on technical leadership and mentorship to engineers, raising the bar on architecture, engineering quality, problem solving, and execution.
• Lead technical design and code reviews and help resolve complex engineering challenges across teams and systems.
• Drive the Build-Operate-Transfer model by incubating new AI products, hardening them for production, and partnering with business-aligned technology teams to transition proven solutions for long-term ownership and scale.
• Ensure AI systems achieve measurable quality, production readiness, operational observability, appropriate safety controls, and sustainable total cost of ownership.
• Identify opportunities for shared AI platforms and abstractions, balancing reusable enterprise capabilities with product-specific requirements.
• Identify and pursue opportunities to apply AI in ways that accelerate workflows, improve decision-making, and create scalable business impact across the firm.
• Engage directly with business stakeholders, product owners, senior partners, and technology leaders to understand priorities and shape solution and technical direction.
• Translate complex and ambiguous business needs into robust AI solutions and architectures that support both immediate value and broader enterprise adoption.
• Apply strong product and engineering judgment to balance innovation, scalability, business value, risk, cost, security, and long-term maintainability.
• Influence technical decisions across initiatives and communicate complex AI concepts, architectures, risks, and trade-offs effectively to technical and non-technical audiences.

Benefits

• Competitive compensation and annual bonus eligibility
• A generous retirement plan
• Hybrid and flexible work opportunities
• Health and wellness benefits, including online therapy
• Paid time off for vacation, illness, medical appointments, and volunteering days
• Family-care resources, including fertility and adoption benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Senior