Lead Applied AI Engineer II - ServiceNow

DataJobs; Nashville (TN); On-site; USD 150,000 - 190,000; Full time

Job summary

Deloitte seeks a senior software engineer to lead applied AI and agentic engineering for high-visibility, full-stack products from concept to production. You will own architecture, maintain cost discipline, mentor teammates, and collaborate across product, UX, and delivery teams to ship outcomes.

The role emphasizes hands-on coding, modern software practices, and continual learning in AI/SSDL lifecycle. On-site collaboration is expected in Nashville.

Qualifications

• Bachelor's degree in CS, software engineering, data science or related field.
• 6+ years of full-stack software engineering experience with listed technologies.
• 3+ years building AI/ML and agentic applications with GenAI, RAG, vector databases, and AI orchestration.
• 3+ years cloud-native engineering with Azure/AWS/GCP and cost-aware practices (FinOps).
• 1+ years establishing engineering standards and leading adoption.
• Experience with design diagrams and AI-augmented development.

Responsibilities

• Lead end-to-end engineering from concept to production.
• Own inference, token, and cloud cost for developed solutions.
• Mentor engineers and ensure code quality and KPI targets.
• Collaborate across product management, UX, and delivery teams.
• Create scalable, testable, compliant architecture and components.
• Drive lean, fast experimentation to validate customer value.

Skills

JavaScript/TypeScript

Angular

React

NodeJS

Python

SQL/NoSQL

REST/API

ServiceNow

LangChain

LangGraph

AI/GenAI

Unit/Integration Testing

Education

Bachelor's degree

Tools

ServiceNow NowAssist

Infra-as-code

FinOps

GitHub

SonarQube

MLflow

ATF

Job description

Join Deloitte to lead applied AI and agentic engineering work for high-visibility, full-stack products, with end-to-end delivery from concept through production.

Responsibilities

• Drive a culture of accountability for customer and business outcomes, including the cost of achieving them.
• Design and deliver engineering solutions for complex problems with valuable outcomes, emphasizing high-quality, lean designs and implementations.
• Own inference, token, and cloud cost for what you build.
• Act as a technical advocate to ensure code integrity, feasibility, and alignment with business and customer goals.
• Lead requirement analysis; produce low-level architecture and component design.
• Own development, testing, integrations, and ongoing support for delivered components.
• Maintain accountability for the integrity of architecture and technical stack against enterprise standards and strategy.
• Manage dependencies and take responsibility for code design, implementation, quality, data, and ongoing maintenance and operations.
• Stay hands-on, self-directed, and continuously learn new approaches, languages, and frameworks.
• Create technical specifications and write scalable, supportable code.
• Review engineers’ code, mentor team members, and help ensure all quality KPIs are met or exceeded.
• Use collaborative communication to work effectively across diverse teams.
• Build lean solutions using rapid, inexpensive experimentation to address customer needs.
• Engage with customers and product teams before, during, and after delivery to ensure timely delivery of the right solution.
• Adopt an evidence-led, action-oriented approach to address complexity and uncertainty.
• Collaborate with empowered cross-functional teams including product management, experience, and delivery.
• Balance feasibility, viability, usability, and value by integrating diverse perspectives and driving consensus.
• Demonstrate deep expertise in modern software engineering practices, including AI and Agentic SSDLC, to enable daily product deployments with full automation from discovery to production to operations and quality checks across the SSDLC lifecycle.
• Serve as a role model for solutioning and product delivery using these techniques.
• Build domain knowledge quickly and translate business and user needs, architectures, and UX/UI designs into technical specifications and code.
• Support teammates, prioritize quality, and focus on tech debt payoff.
• Communicate complex technical concepts clearly and influence teammates and product teams through evidence-backed trade-offs.
• Create coherent technical narratives that align solutions with business objectives.
• Collaborate with product engineering teams at all organizational levels, including customers as needed.
• Build and maintain constructive relationships to foster co-creation and shared momentum toward product goals.
• Align perspectives and drive consensus on feasible solutions.

Requirements

• Bachelor’s degree in computer science, software engineering, data science, machine learning, or a related discipline.
• 6+ years of full-stack software engineering experience, including most of: JavaScript/TypeScript, Angular, React, NodeJS, Python, SQL/NoSQL, REST/API integrations, ServiceNow application development and deployment patterns, LangChain, LangGraph, and unit and integration testing frameworks.
• 3+ years building AI/ML and agentic applications, including hands‑on GenAI across LLM integration (OpenAI, Anthropic, or open‑source models), RAG pipelines, prompt engineering, vector databases, evaluations, and AI agent orchestration, plus applied AI capabilities on ServiceNow.
• 3+ years cloud‑native engineering experience using FaaS, PaaS, micro‑services, or enterprise platform deployment models, including Azure, AWS, GCP, and AI/ML services such as ServiceNow NowAssist, along with application‑level infrastructure-as-code and cost‑aware engineering (FinOps accountability).
• 1+ years establishing engineering standards, including leading, mentoring, and guiding adoption and continuous improvement.
• Software engineering experience with Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentations, plus AI‑augmented spec‑driven development.
• Experience with methodologies & tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, Automated Test Framework (ATF), MLflow, and agentic AI frameworks (for example ServiceNow NASK, MCP, LangFuse, LangSmith, or equivalent multi‑agent orchestration tools).
• ServiceNow engineering experience including platform architecture, workflow automation, integrations, and AI‑enabled ServiceNow capabilities, with ability to translate product needs into scalable enterprise solutions.
• Preferred certifications may include ServiceNow Certified System Administrator, Certified Application Developer, CIS-HRSD, CIS-Data Foundations, CIS-ITSM, CIS-IRM, CIS-SPM, AI/GenAI-focused ServiceNow credentials, or relevant cloud/AI certifications.
• Must be located within commutable distance to the role location.
• Ability to work in the local office at least 3 days per week.

Technologies

• JavaScript/TypeScript, Angular, React, NodeJS, Python, SQL/NoSQL
• REST/API integrations, ServiceNow application development and deployment patterns
• LangChain, LangGraph
• OpenAI, Anthropic, RAG pipelines, prompt engineering, vector databases, AI agent orchestration
• ServiceNow, ServiceNow NowAssist, infrastructure-as-code, FinOps
• FaaS, PaaS, micro‑services; Azure, AWS, GCP
• Business Context Diagrams (BCD), OOP/OOD, data structures, algorithms, code instrumentations
• Unit and integration testing frameworks, XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube
• Automated Test Framework (ATF), MLflow
• ServiceNow NASK, MCP, LangFuse, LangSmith
• ServiceNow certifications including System Administrator and Certified Application Developer; CIS-HRSD, CIS-Data Foundations, CIS-ITSM, CIS-IRM, CIS-SPM; AI/GenAI-focused ServiceNow credentials

Other

• Travel: 10% average, based on work and products built.
• Limited immigration sponsorship may be available.
• Must be located within commutable distance and work onsite minimum of 3 days per week.