Tax Associate, State and Local Tax - Winter 2027 (Cleveland)

Job Summary: The SALT Associate will be responsible for basic research and analysis of state and local tax (SALT) issues, along with utilization of tax software in the completion of basic tax returns and other tax filings and documents. In this role, the Tax Associate, State and Local Taxation will have the opportunity to utilize their educational background while working side-by-side with more experienced Tax members who will provide direction and coaching related a range of state and local tax laws and resources. Job Duties: Research Identifies simple situations when research is necessary providing an outline of the issue(s) and the appropriate source of research to be conducted Analyzes researched facts and the sources utilized prior to composing a detailed report of the research findings Prepares WTA and tax returns as appropriate Tax Compliance Participates in the preparation, filing and completion of voluntary disclosure agreements for sales and use tax; income tax and unclaimed property Drafts tax memorandums, tax opinions and other documentation on various tax issues Assists in the drafting of responses to notices from state taxing authorities Prepares modeling for tax and unclaimed property exposure analysis Participates in the audit defense of client returns and tax positions Ensures all data needed to comply with filing requirements is obtained and identifies missing items to need for preparation of assigned tax returns Monitors current tax law changes and applies appropriately to the preparation of assigned tax returns Manages collection and retention of all appropriate workpapers for assigned clients Tax Consulting Develops, recommends and implements standard tax methods to provide clients with maximum tax benefits related to current and future tax obligations Utilizes online research tools, prior tax returns, interviews with client personnel and other resources to gather pertinent tax information related to assigned clients Continues building tax knowledge by monitoring relevant tax laws and educating oneself on firm tax strategies and Tax Planning Ideas (TPIs) Tax Related Software Utilizes Caseware, GoSystems, tax research databases and other tax-related software in the completion of assigned tasks Tax Specialization Develops an in-depth understanding of the technical and practical issues and opportunities regarding SALT tax benefits ASC740-10 Understands and applies industry standards, along with firm policies and BDO Tax Quality Manual requirements as they relate to FAS 109 and FIN48, as well as FAS5 for sales tax and unclaimed properties Strategy Development Assists in the preparation of studies of tax implications to identify alternative courses of actions to benefits clients Develops an understanding of the impact of a client’s business objectives as it relates to the client’s tax situation Other duties as required Supervisory Responsibilities: N/A Qualifications, Knowledge, Skills and Abilities: Education: Bachelors degree required; focus in Accounting, preferred Masters degree in Accounting/Taxation or J.D., preferred Experience: Prior internship or other work experience within an accounting setting or public accounting, preferred License/Certifications: Eligible to sit for the CPA exams; progress towards admission to practice in a U.S. jurisdiction; progress towards Internal Revenue Service Enrolled Agent (“EA”) (or progress towards the equivalent of one of these designations) upon starting employment, preferred Software: Proficient in the use of Microsoft Office Suite, specifically Word, Excel and PowerPoint, required Language: N/A Other Knowledge, Skills & Abilities: Excellent verbal and written communication skills Strong analytical and basic research skills Solid organizational skills especially ability to meet project deadlines with a focus on details Ability to successfully multi-task while working independently or within a group environment Proven ability to work in a deadline-driven environment and handle multiple projects simultaneously Ability to prepare simple tax returns Basic knowledge of appropriate application of tax standards to ensure effective and efficient delivery of tax services Basic knowledge of sources of relevant information utilized in tax filings as well as the most widely-used filing forms and awareness of other less widely used forms Basic knowledge and understanding of cause / effect for taxable conditions on clients and the potential tax issues Basic knowledge of accounting theory, filing methodologies, and frequencies for sales tax returns Individual salaries that are offered to a candidate are determined after consideration of numerous factors including but not limited to the candidate’s qualifications, experience, skills, and geography. California Range: $85,000 - $120,000 Colorado Range: $78,000 - $120,000 Illinois Range: $80,000 - $100,000 Maryland Range: $85,000 - $100,000 Massachusetts Range: $85,000 - $120,000 Minnesota Range: $72,000 - $100,000 New Jersey Range: $80,000 - $100,000 NYC/Long Island/Westchester Range: $85,000 - $120,000 Ohio Range: $71,000 - $75,000 Virginia Range: $83,000 - $87,000 Washington Range: $78,000 - $120,000 Washington DC Range: $85,000 - $100,000

AI Agent Trajectory Annotator and Reviewer

Type: Contract, hourly Location: Remote Hours: 20–30 per week Pay: $20–30/hour, based on experience and language coverage Start: Immediate ABOUT THE ROLE We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision. You will do two jobs, and you should expect either on any given day. •Annotate — Read a trajectory nobody has looked at yet and judge it step by step. • Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it. TASKS YOU'LL SEE • Feature build — Add a working feature to a live library without breaking anything that already worked. • Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects. • Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them. Mostly Python and Go, with some Rust, C, and Ct. A trajectory runs about 100 steps. WHAT YOU JUDGE IN A TRAJECTORY • Was the command right for the state the environment was actually in? • Did the agent read the previous output correctly? • Was the step wrong, or only inefficient — these are scored differently. • Where did the run first go off course — usually earlier than where it visibly broke. • Did the agent notice its own mistake and recover, or keep building on a false assumption? • Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)? WHAT WE NEED FROM YOU • Experience — 2 years in software engineering, DevOps, or site reliability, with real debugging in real codebases. • Languages — Strong in Python or Go, and able to read a language you've never used. • Linux — Comfortable with logs, running processes, build failures, and containers. • Workflow — Everyday Git, diffs, pull requests, and issue tracking. • Debugging — Able to work with no test suite and no error message pointing at the cause. • Focus — Able to hold context across a long run, because step 74 can depend on step 12. • Writing — Clear English, since every judgement needs an explanation another engineer can check.

AI Agent Trajectory Annotator and Reviewer

Type: Contract, hourly Location: Remote Hours: 20–30 per week Pay: $20–30/hour, based on experience and language coverage Start: Immediate ABOUT THE ROLE We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision. You will do two jobs, and you should expect either on any given day. •Annotate — Read a trajectory nobody has looked at yet and judge it step by step. • Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it. TASKS YOU'LL SEE • Feature build — Add a working feature to a live library without breaking anything that already worked. • Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects. • Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them. Mostly Python and Go, with some Rust, C, and Ct. A trajectory runs about 100 steps. WHAT YOU JUDGE IN A TRAJECTORY • Was the command right for the state the environment was actually in? • Did the agent read the previous output correctly? • Was the step wrong, or only inefficient — these are scored differently. • Where did the run first go off course — usually earlier than where it visibly broke. • Did the agent notice its own mistake and recover, or keep building on a false assumption? • Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)? WHAT WE NEED FROM YOU • Experience — 2 years in software engineering, DevOps, or site reliability, with real debugging in real codebases. • Languages — Strong in Python or Go, and able to read a language you've never used. • Linux — Comfortable with logs, running processes, build failures, and containers. • Workflow — Everyday Git, diffs, pull requests, and issue tracking. • Debugging — Able to work with no test suite and no error message pointing at the cause. • Focus — Able to hold context across a long run, because step 74 can depend on step 12. • Writing — Clear English, since every judgement needs an explanation another engineer can check.

AI Agent Trajectory Annotator and Reviewer

Type: Contract, hourly Location: Remote Hours: 20–30 per week Pay: $20–30/hour, based on experience and language coverage Start: Immediate ABOUT THE ROLE We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision. You will do two jobs, and you should expect either on any given day. •Annotate — Read a trajectory nobody has looked at yet and judge it step by step. • Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it. TASKS YOU'LL SEE • Feature build — Add a working feature to a live library without breaking anything that already worked. • Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects. • Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them. Mostly Python and Go, with some Rust, C, and Ct. A trajectory runs about 100 steps. WHAT YOU JUDGE IN A TRAJECTORY • Was the command right for the state the environment was actually in? • Did the agent read the previous output correctly? • Was the step wrong, or only inefficient — these are scored differently. • Where did the run first go off course — usually earlier than where it visibly broke. • Did the agent notice its own mistake and recover, or keep building on a false assumption? • Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)? WHAT WE NEED FROM YOU • Experience — 2 years in software engineering, DevOps, or site reliability, with real debugging in real codebases. • Languages — Strong in Python or Go, and able to read a language you've never used. • Linux — Comfortable with logs, running processes, build failures, and containers. • Workflow — Everyday Git, diffs, pull requests, and issue tracking. • Debugging — Able to work with no test suite and no error message pointing at the cause. • Focus — Able to hold context across a long run, because step 74 can depend on step 12. • Writing — Clear English, since every judgement needs an explanation another engineer can check.

AI Agent Trajectory Annotator and Reviewer

Type: Contract, hourly Location: Remote Hours: 20–30 per week Pay: $20–30/hour, based on experience and language coverage Start: Immediate ABOUT THE ROLE We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision. You will do two jobs, and you should expect either on any given day. •Annotate — Read a trajectory nobody has looked at yet and judge it step by step. • Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it. TASKS YOU'LL SEE • Feature build — Add a working feature to a live library without breaking anything that already worked. • Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects. • Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them. Mostly Python and Go, with some Rust, C, and Ct. A trajectory runs about 100 steps. WHAT YOU JUDGE IN A TRAJECTORY • Was the command right for the state the environment was actually in? • Did the agent read the previous output correctly? • Was the step wrong, or only inefficient — these are scored differently. • Where did the run first go off course — usually earlier than where it visibly broke. • Did the agent notice its own mistake and recover, or keep building on a false assumption? • Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)? WHAT WE NEED FROM YOU • Experience — 2 years in software engineering, DevOps, or site reliability, with real debugging in real codebases. • Languages — Strong in Python or Go, and able to read a language you've never used. • Linux — Comfortable with logs, running processes, build failures, and containers. • Workflow — Everyday Git, diffs, pull requests, and issue tracking. • Debugging — Able to work with no test suite and no error message pointing at the cause. • Focus — Able to hold context across a long run, because step 74 can depend on step 12. • Writing — Clear English, since every judgement needs an explanation another engineer can check.

AI Agent Trajectory Annotator and Reviewer

Type: Contract, hourly Location: Remote Hours: 20–30 per week Pay: $20–30/hour, based on experience and language coverage Start: Immediate ABOUT THE ROLE We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision. You will do two jobs, and you should expect either on any given day. •Annotate — Read a trajectory nobody has looked at yet and judge it step by step. • Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it. TASKS YOU'LL SEE • Feature build — Add a working feature to a live library without breaking anything that already worked. • Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects. • Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them. Mostly Python and Go, with some Rust, C, and Ct. A trajectory runs about 100 steps. WHAT YOU JUDGE IN A TRAJECTORY • Was the command right for the state the environment was actually in? • Did the agent read the previous output correctly? • Was the step wrong, or only inefficient — these are scored differently. • Where did the run first go off course — usually earlier than where it visibly broke. • Did the agent notice its own mistake and recover, or keep building on a false assumption? • Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)? WHAT WE NEED FROM YOU • Experience — 2 years in software engineering, DevOps, or site reliability, with real debugging in real codebases. • Languages — Strong in Python or Go, and able to read a language you've never used. • Linux — Comfortable with logs, running processes, build failures, and containers. • Workflow — Everyday Git, diffs, pull requests, and issue tracking. • Debugging — Able to work with no test suite and no error message pointing at the cause. • Focus — Able to hold context across a long run, because step 74 can depend on step 12. • Writing — Clear English, since every judgement needs an explanation another engineer can check.

AI Agent Trajectory Annotator and Reviewer

Type: Contract, hourly Location: Remote Hours: 20–30 per week Pay: $20–30/hour, based on experience and language coverage Start: Immediate ABOUT THE ROLE We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision. You will do two jobs, and you should expect either on any given day. •Annotate — Read a trajectory nobody has looked at yet and judge it step by step. • Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it. TASKS YOU'LL SEE • Feature build — Add a working feature to a live library without breaking anything that already worked. • Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects. • Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them. Mostly Python and Go, with some Rust, C, and Ct. A trajectory runs about 100 steps. WHAT YOU JUDGE IN A TRAJECTORY • Was the command right for the state the environment was actually in? • Did the agent read the previous output correctly? • Was the step wrong, or only inefficient — these are scored differently. • Where did the run first go off course — usually earlier than where it visibly broke. • Did the agent notice its own mistake and recover, or keep building on a false assumption? • Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)? WHAT WE NEED FROM YOU • Experience — 2 years in software engineering, DevOps, or site reliability, with real debugging in real codebases. • Languages — Strong in Python or Go, and able to read a language you've never used. • Linux — Comfortable with logs, running processes, build failures, and containers. • Workflow — Everyday Git, diffs, pull requests, and issue tracking. • Debugging — Able to work with no test suite and no error message pointing at the cause. • Focus — Able to hold context across a long run, because step 74 can depend on step 12. • Writing — Clear English, since every judgement needs an explanation another engineer can check.

AI Agent Trajectory Annotator and Reviewer

Type: Contract, hourly Location: Remote Hours: 20–30 per week Pay: $20–30/hour, based on experience and language coverage Start: Immediate ABOUT THE ROLE We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision. You will do two jobs, and you should expect either on any given day. •Annotate — Read a trajectory nobody has looked at yet and judge it step by step. • Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it. TASKS YOU'LL SEE • Feature build — Add a working feature to a live library without breaking anything that already worked. • Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects. • Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them. Mostly Python and Go, with some Rust, C, and Ct. A trajectory runs about 100 steps. WHAT YOU JUDGE IN A TRAJECTORY • Was the command right for the state the environment was actually in? • Did the agent read the previous output correctly? • Was the step wrong, or only inefficient — these are scored differently. • Where did the run first go off course — usually earlier than where it visibly broke. • Did the agent notice its own mistake and recover, or keep building on a false assumption? • Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)? WHAT WE NEED FROM YOU • Experience — 2 years in software engineering, DevOps, or site reliability, with real debugging in real codebases. • Languages — Strong in Python or Go, and able to read a language you've never used. • Linux — Comfortable with logs, running processes, build failures, and containers. • Workflow — Everyday Git, diffs, pull requests, and issue tracking. • Debugging — Able to work with no test suite and no error message pointing at the cause. • Focus — Able to hold context across a long run, because step 74 can depend on step 12. • Writing — Clear English, since every judgement needs an explanation another engineer can check.

AI Agent Trajectory Annotator and Reviewer

Type: Contract, hourly Location: Remote Hours: 20–30 per week Pay: $20–30/hour, based on experience and language coverage Start: Immediate ABOUT THE ROLE We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision. You will do two jobs, and you should expect either on any given day. •Annotate — Read a trajectory nobody has looked at yet and judge it step by step. • Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it. TASKS YOU'LL SEE • Feature build — Add a working feature to a live library without breaking anything that already worked. • Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects. • Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them. Mostly Python and Go, with some Rust, C, and Ct. A trajectory runs about 100 steps. WHAT YOU JUDGE IN A TRAJECTORY • Was the command right for the state the environment was actually in? • Did the agent read the previous output correctly? • Was the step wrong, or only inefficient — these are scored differently. • Where did the run first go off course — usually earlier than where it visibly broke. • Did the agent notice its own mistake and recover, or keep building on a false assumption? • Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)? WHAT WE NEED FROM YOU • Experience — 2 years in software engineering, DevOps, or site reliability, with real debugging in real codebases. • Languages — Strong in Python or Go, and able to read a language you've never used. • Linux — Comfortable with logs, running processes, build failures, and containers. • Workflow — Everyday Git, diffs, pull requests, and issue tracking. • Debugging — Able to work with no test suite and no error message pointing at the cause. • Focus — Able to hold context across a long run, because step 74 can depend on step 12. • Writing — Clear English, since every judgement needs an explanation another engineer can check.