Applied AI Engineer II

Join Deloitte in Atlanta as an Applied AI Engineer II to build full stack products powered by GenAI and agentic capabilities. Collaborate across product management, experience, and delivery teams to take ideas from concept to production and deliver outcomes that matter for customers and the business. This onsite role offers a competitive salary range of USD 102,500 – 188,900 per year and includes a discretionary annual incentive program that recognizes impact.

Responsibilities

• Outcome-Driven Accountability Own measurable customer and business outcomes and the cost of delivering them. Create engineering solutions to tackle complex problems with lean, high‑quality designs, and take responsibility for inference, tokens, and cloud spend.
• Technical Leadership and Advocacy Serve as the technical champion for products, safeguarding code integrity and alignment with business and customer goals. Contribute across requirement analysis, component design, development, testing, integrations, and support.
• Engineering Craftsmanship Maintain code‑design integrity, fidelity to architecture, quality, data stewardship, and ongoing operations. Be hands‑on and proactive, continuously learning new approaches, languages, and frameworks. Produce technical specifications and high‑quality, scalable code that meets quality KPIs, collaborating effectively with diverse teams.
• Customer‑Centric Engineering Develop lean solutions through rapid, cost‑effective experimentation. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
• Incremental and Iterative Delivery Favor action and evidence over extensive planning. Navigate complexity with a forward‑leaning approach to deliver lean, maintainable solutions.
• Cross‑Functional Collaboration and Integration Work with empowered product management, experience, and delivery teams to balance feasibility, viability, usability, and value. Foster collaboration that enhances team synergy and innovation.
• Advanced Technical Proficiency Apply modern software engineering practices, including AI and agentic SDLC, to deliver daily deployments with full automation from discovery to production to operations, with quality checks throughout the lifecycle. Model these techniques to improve solutioning and delivery, continually advancing full lifecycle product development.
• Domain Expertise Quickly acquire domain knowledge relevant to the business or product and translate business needs, architectures, and UX/UI designs into technical specifications and code. Be a reliable, quality‑focused team member who supports teammates and helps reduce tech debt.
• Effective Communication and Influence Articulate complex technical concepts clearly and persuasively. Build evidence‑based narratives that align technical solutions with business objectives and inspire teammates and product teams.
• Engagement and Collaborative Co‑Creation Engage with product engineering teams at all levels and with customers as needed. Build constructive relationships that foster co‑creation and momentum toward product goals, aligning diverse perspectives to feasible solutions.

Requirements

• Ability to work independently and collaboratively within a team
• Strong written and verbal communication skills
• Meticulous attention to detail and quality of work
• Ability to build and sustain professional relationships
• Experience leading projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast paced environment
• Strong interpersonal skills and professional demeanor
• Proven ability to meet deadlines
• Ability to provide clear guidance to others
• Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline; practical experience highly valued
• 3+ years of experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, and unit testing frameworks
• 2+ years of experience building AI/ML and agentic applications, with hands‑on GenAI experience across LLM integrations (OpenAI, Anthropic, or open‑source models), RAG pipelines, prompt engineering, vector databases, evaluations, and AI agent orchestration
• 2+ years of cloud‑native engineering using FaaS, PaaS, or microservices on Azure, AWS, or GCP, including AI/ML services (Azure OpenAI, AWS Bedrock, Vertex AI) and infrastructure‑as‑code with FinOps accountability
• Prior software engineering experience with business context diagrams, sequence/activity/state/entity relationships, OOP/OOD, data structures, algorithms, and AI‑augmented spec‑driven development
• Experience with XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (e.g., LangFuse, LangSmith) to deliver high‑quality products rapidly
• Willingness to travel approximately 10% depending on project needs
• Limited immigration sponsorship may be available

Technologies

• Angular, React, NodeJS, Python, C#, .NET, Java
• SQL/NoSQL, PyTorch, TensorFlow
• LangChain, LangGraph
• OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI
• Azure, GCP, AWS
• GitHub, ADO, SonarQube, MLflow
• LangFuse, LangSmith

Benefits

• Discretionary annual incentive program