Lead AI Software Engineer – T. Rowe Price Lab

Jobtailor

Maryland

On-site

USD 180,000 - 240,000

Full time

4 days ago

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Job summary

Jobtailor seeks a Senior AI/ML Systems Architect to lead architecture, design, deployment, and evolution of production-grade AI agents and intelligent systems. You will define standards for production AI, including observability, guardrails, and security, while guiding reusable capabilities and platform components.

You will influence technical decisions, mentor engineers, and partner with business stakeholders to deliver scalable AI solutions with measurable impact.

Qualifications

8+ years of progressive software engineering experience.
Strong OO programming in Python, Java, or JavaScript/TypeScript.
Experience leading technical delivery across teams or major initiatives.
Deep hands-on experience designing AI-enabled systems in production.
Expertise in agent orchestration, tool calling, retrieval-based systems, and prompt engineering.
Experience with cloud-native solutions on AWS, containerized microservices, and APIs.
Knowledge of evaluation, observability, guardrails, and failure handling for AI systems.
Excellent communication and ability to influence stakeholders.
Experience mentoring engineers.

Responsibilities

Lead the architecture, design, development, deployment, and evolution of production-grade AI agents and intelligent systems.
Set technical direction across models, orchestration, retrieval, tools, data, infrastructure, latency, cost, security, reliability, and maintainability.
Lead teams through complex AI problems from experimentation to production scale.
Define engineering standards for production AI, including evaluation, testing, observability, guardrails, failure handling, security, and responsible deployment.
Guide reusable AI capabilities and shared platform components.
Evaluate emerging models, frameworks, tools, and AI engineering approaches.
Provide hands-on technical leadership and mentorship.
Lead technical design and code reviews.
Incubate AI products, harden them for production, and transition solutions to business teams.
Ensure AI systems achieve measurable quality, production readiness, observability, safety controls, and sustainable cost of ownership.
Identify opportunities to apply AI to accelerate workflows and decision-making.
Engage with business stakeholders, product owners, senior partners, and technology leaders.
Translate ambiguous business needs into robust AI solutions and architectures.
Influence technical decisions and communicate AI concepts, architectures, risks, and trade-offs.

Skills

Python

Java

JavaScript/TypeScript

AI systems

Technical leadership

Mentoring

Observability

Security

Continuous delivery

AWS

Containerization

APIs

Microservices

Agent orchestration

Education

CS degree or related field

Tools

AWS

Containerization

APIs

Microservices

AI frameworks

Job description

Lead the architecture, design, development, deployment, and evolution of production-grade AI agents and intelligent systems
Set technical direction across models, orchestration, retrieval, tools, data, infrastructure, latency, cost, security, reliability, and maintainability
Lead teams through complex AI problems from experimentation and architecture through production adoption and scale
Define engineering standards for production AI, including evaluation, testing, observability, guardrails, failure handling, security, and responsible deployment
Guide reusable AI capabilities and shared platform components
Evaluate emerging models, frameworks, tools, and AI engineering approaches
Provide hands‑on technical leadership and mentorship
Lead technical design and code reviews
Incubate AI products, harden them for production, and transition proven solutions to business‑aligned technology teams
Ensure AI systems achieve measurable quality, production readiness, observability, safety controls, and sustainable cost of ownership
Identify opportunities to apply AI to accelerate workflows, improve decision‑making, and create scalable business impact
Engage with business stakeholders, product owners, senior partners, and technology leaders
Translate ambiguous business needs into robust AI solutions and architectures
Influence technical decisions and communicate AI concepts, architectures, risks, and trade‑offs to technical and non‑technical audiences

Requirements

BS or MS in Computer Science or a related technical field, or equivalent practical experience
8+ years of progressive software engineering experience
Extensive hands‑on experience in object‑oriented languages such as Python, Java, or JavaScript/TypeScript
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
Expertise in agent orchestration, tool/function calling, retrieval‑based systems, prompt and context engineering, evaluation, observability, guardrails, and failure handling
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
Exceptional analytical, problem‑solving, architecture, and system‑design skills
Demonstrated ability to lead engineers through complex and ambiguous technical challenges
Experience with automated testing, code reviews, observability, security, and continuous delivery
Strong communication and influence skills
Experience mentoring engineers
FINRA licenses are not required and will not be supported for this role

Core Competencies

Demonstrates expertise in leading the architecture and development of AI systems, with a strong focus on production readiness, observability, and security. Proven ability to mentor teams and translate complex business needs into effective AI solutions.

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