Senior Consultant - Software Engineer (Agentic Engineering) - Tax Technology

Deloitte•Washington, DC

121d•$102,750 - $195,250•Hybrid

About The Position

Are you someone who wants hands-on experience building the tooling and knowledge infrastructure behind an agentic software development lifecycle? Are you ready to take the next step in your career by building integrations and knowledge bases that other engineering teams will depend on every day? Are you ready to work alongside experienced engineers on a small, high-visibility platform team? If the answer to all of the above questions is “Yes,” come join the world's leading professional services firm. If you are prepared and poised to take the next step in your career, you can help build the platform that powers agentic software delivery across a global business. Then we want to talk to you.

Requirements

Ability to perform job responsibilities within a hybrid work model that requires US Tax professionals to co-locate in person 2 – 3 days per week
Bachelor’s degree in computer science, information technology, engineering, or a related field.
3+ years of hands-on Python experience, including building APIs, writing automated tests, debugging, and scripting for automation.
Experience with SQL and data preprocessing, including data cleaning, feature handling, and working with both structured and unstructured data.
Working knowledge of core data science libraries such as pandas, NumPy, and scikit-learn, with basic exposure to visualization libraries such as Matplotlib or Seaborn for analysis and evaluation.
Solid understanding of LLM and generative AI fundamentals, including prompting, embeddings, retrieval-augmented generation, vector databases, evaluation methods, guardrails, and hallucination management.
Experience building chains, tools, or agents with LangChain, LangGraph, or a comparable orchestration framework for stateful AI workflows.
Experience using AWS services programmatically via Boto3, including S3, Lambda, Bedrock, DynamoDB, and Agent Core, to support deployment workflows.
Experience with API integrations across at least two enterprise platforms (for example, Azure DevOps, ServiceNow, Jira, Confluence).
Experience with backend deployment practices, including FastAPI, Docker, CI/CD, logging, and monitoring.
Limited immigration sponsorship may be available.
Ability to travel up to 20%, on average, based on the work you do and the clients and industries/sectors you serve.
One of the following active accreditations obtained in process, or willing/able to obtain: Licensed CPA in state of practice/primary office if eligible to sit for the CPA; If not CPA eligible: Licensed attorney, Enrolled Agent, AWS Certified Solutions Architect, Certified Information Systems Security Professional (CISSP), Certified SAFe® Agile Software Engineer, Certified SAFe® DevOps Practitioner, ISTQB (International Software Testing Qualifications Board), Microsoft Azure, Microsoft Certified Solutions Developer (MCSD), Oracle Certified Professional

Nice To Haves

Experience building usable interfaces for AI-powered tools using Streamlit, Gradio, React, or similar front-end frameworks
Familiarity with LLM evaluation and AI development workflows using tools such as DeepEval, RAGAS, AWS Kiro, GitHub Copilot, Claude Code, or similar.
Experience integrating platforms and automation workflows using Azure DevOps and ServiceNow APIs, webhooks, or connectors.
Prior experience supporting internal engineering teams or transformation efforts, including modernization initiatives and translating technical program management needs such as risk and dependency tracking into working software.
Strong software engineering and collaboration skills, including writing clean, well-tested code, contributing constructively in code reviews, and communicating effectively across technical and non-technical teams.

Responsibilities

Build data and knowledge foundations that prepare structured and unstructured information for the LLM Wiki and AWS Bedrock-managed knowledge bases.
Engineer grounded AI capabilities by developing retrieval-augmented generation pipelines, agentic workflows, evaluation harnesses, and guardrails that improve accuracy, reliability, and safety.
Connect the agentic software development lifecycle by integrating AWS Kiro, Azure DevOps, ServiceNow, and related platforms to automate the flow of program artifacts, defects, pull requests, and code updates.
Develop production-ready platform capabilities including backend services, APIs, lightweight user interfaces, deployment pipelines, logging, and monitoring that enable teams to use tools without direct API access.
Deliver iterative, well-documented solutions that improve visibility into program risks and dependencies, reduce manual effort, and help engineering and technical program management teams adopt and extend the platform.