Applied AI Engineer II

At Deloitte, the on-site Applied AI Engineer II in Atlanta helps turn ideas into full‑stack products powered by GenAI and agentic capabilities. You’ll collaborate across product and AI investments to deliver outcomes that matter, guiding ideas from concept through production with a strong emphasis on quality and impact. This role offers a competitive annual salary range of USD 102,500 to 188,900, onsite work in Atlanta, and eligibility for a discretionary annual incentive program. You’ll join a team that values practical engineering, measurable results, and close collaboration with cross‑functional partners.

Responsibilities

• Outcome driven accountability: develop engineering solutions that address complex problems with meaningful business value, maintaining lean designs and controlling inference, token, and cloud costs.
• Technical leadership and advocacy: act as the technical champion for products, ensuring code integrity, feasibility, and alignment with business and customer goals; participate across requirements, design, development, testing, integrations, and support.
• Engineering craftsmanship: uphold code and design integrity, align implementation with architecture and tech stack, ensure quality and maintainability; be hands‑on, continuously learn new approaches, and produce technical specifications and scalable, well‑documented code that meets quality KPIs; collaborate effectively with diverse teams.
• Customer centric engineering: develop lean solutions through rapid, low‑cost experimentation to solve customer needs; engage with customers and product teams before, during, and after delivery to ensure timely and appropriate solutions.
• Incremental and iterative delivery: prioritize action and evidence over extensive planning; navigate complexity with a forward‑leaning approach to deliver maintainable solutions.
• Cross‑functional collaboration and integration: work with product management, design, and delivery teams; balance feasibility, viability, usability, and value by integrating diverse perspectives; foster a collaborative environment that enhances innovation.
• Advanced technical proficiency: apply modern software engineering practices including AI and agentic SSDLC to deliver frequent product deployments with full automation from discovery through production and operations, supported by quality checks throughout the lifecycle; model and promote these techniques to improve solutioning and delivery; focus on continuous improvement and lifecycle understanding.
• 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; contribute as a flexible, quality‑focused team member, mindful of tech debt payoff.
• Effective communication and influence: articulate complex technical concepts clearly, persuading teammates and product teams with evidence and well‑structured trade‑offs; craft narratives that align technical solutions with business objectives.
• Engagement and collaborative co‑creation: engage with product engineering teams at all levels and with customers as needed; cultivate constructive relationships and a culture of co‑creation to achieve product goals.

Requirements

• Ability to work independently and as part of a team
• Strong written and verbal communication skills
• Meticulous attention to detail and quality of work
• Ability to build and sustain professional relationships
• Ability to lead projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast paced environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines and provide clear guidance to others
• Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline
• 3+ years of experience with Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, and unit testing frameworks
• 2+ years building AI/ML and agentic applications with hands‑on GenAI experience across LLM integration (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
• Experience with business context diagrams, sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and AI‑augmented spec‑driven development
• Familiarity with XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (eg LangFuse, LangSmith) for rapid, high‑quality product delivery
• Ability 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, GitHub, ADO, SonarQube, MLflow
• LangFuse, LangSmith

Benefits

• Discretionary annual incentive program