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Comparable Jobs in Washington (NOW HIRING)

Senior Full Stack Engineer

Washington, DC · On-site

$150 - $250/hr

  • Medical

  • Dental

  • Vision

Develop backend services and APIs using Go, Chi, or comparable backend frameworks. * Build secure application workflows for authentication, authorization, role-based access control, and customer ...

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Comparable information

See Washington salary details

$58.3K

$110.2K

$173.9K

How much do comparable jobs pay per year?

As of Aug 19, 2026, the average yearly pay for comparable in Washington is $110,184.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,600.00 and $117,800.00 per year, depending on experience, location, and employer.

What are comparables in real estate?

Comparables, often referred to as 'comps,' are recently sold properties that are similar in location, size, condition, and features to the property being evaluated. Real estate professionals use comparables to estimate a property's market value by comparing it to these similar properties. This process helps ensure that buyers and sellers have a fair understanding of current market prices. Appraisers, agents, and buyers often rely on comps to make informed decisions during property transactions.

What are the key skills and qualifications needed to thrive as a comparable analyst?

To thrive as a Comparable Analyst, you need strong analytical skills, attention to detail, and a solid understanding of financial and market data, typically supported by a degree in finance, economics, or a related field. Familiarity with financial modeling tools, databases such as Bloomberg or FactSet, and proficiency in Excel are commonly required. Excellent communication, critical thinking, and time management skills help convey insights clearly and manage multiple projects effectively. These skills ensure accurate and timely valuation comparisons, supporting informed decision-making in investment and real estate industries.

What are some common challenges faced by comparable analysts in real estate appraisal, and how can they be addressed?

Professionals conducting comparable analyses for real estate appraisals often face challenges such as limited access to recent or truly similar property data, fluctuating market conditions, and interpreting subjective factors like property condition or neighborhood appeal. Addressing these challenges involves staying current with multiple data sources, maintaining strong relationships with local agents and appraisers, and utilizing advanced analytics tools. Regular communication with team members and continuous professional development can also help ensure accurate and reliable comparisons.

What is considered a comparable job?

A comparable job is a position that has similar responsibilities, required skills, and level of experience as the current or target role. Employers often use comparable jobs to determine salary ranges, job market value, or to assess candidate qualifications. Factors such as industry, job duties, and required certifications are typically considered when identifying comparables.

What are popular job titles related to Comparable jobs in Washington?

For Comparable jobs in Washington, the most frequently searched job titles are:

Infographic showing various Comparable job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 9% Part Time, 2% Temporary, and 6% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $110,184 per year, or $53 per hour.

ID Software/Application Engineer Professional

Environmental and Safety Solutions, Inc.

Reston, VA

Full-time

Posted 5 days ago


Job description

Job Summary

We are seeking a highly skilled Senior Agentic AI Engineer to design, develop, and deploy modern Agentic AI solutions. This role focuses on building production-grade Generative AI applications, multi-agent workflows, and Retrieval-Augmented Generation (RAG) pipelines for enterprise use on Microsoft Azure.

You will collaborate with architects, software engineers, data engineers, and business stakeholders to translate requirements into AI-powered software solutions. The ideal candidate brings hands-on experience developing, evaluating, and operating Agentic AI solutions, supported by strong front-end and back-end engineering fundamentals.
Major Responsibilities

Build Generative AI amp; Retrieval-Augmented Generation LLM Applications

  • Build LLM-powered applications for text generation, summarization, Q amp;A, conversational AI, enterprise knowledge search, and multi-agent orchestration.
  • Develop advanced RAG pipelines using embeddings, Azure AI Search vector and hybrid retrieval, document chunking, metadata filtering, reranking, citations, and grounding techniques with enterprise data.
  • Build secure, reliable integrations between AI agents and enterprise tools, REST APIs, relational databases, and event-driven services.
  • Develop and maintain user-facing AI application experiences using React and TypeScript, and supporting application services using Node.js or comparable back-end technologies.

AI Agents amp; Agentic Automation

  • Design and implement single-agent and multi-agent systems for intelligent automation, decisioning, and complex workflows.
  • Build autonomous and human-in-the-loop agents that plan, reason, act, and interact with tools, APIs, enterprise data, and event-driven systems.
  • Develop agentic workflows using Microsoft Agent Framework, Azure AI Foundry services, or comparable modern orchestration frameworks.
  • Implement configuration-driven agent behavior, prompt and tool management, authorization boundaries, and resilient error-handling patterns.
  • Define and automate evaluation approaches for agent quality, including groundedness, relevance, citation quality, safety, and regression testing.

Instrument agent workflows for traces, tool calls, latency, token usage, errors, and operational metrics using OpenTelemetry, Application Insights, or comparable observability platforms.

  • Build highly scalable, secure, containerized solutions with CI/CD, health checks, horizontal scaling, and production monitoring.

Education and Experience Requirements:

  • Requires a bachelor's degree (or international equivalent) and 8+ years of relevant software engineering experience.
  • 2-3 years of hands-on Generative AI, LLM application, or Agentic AI solution development experience.
  • Strong software engineering background with experience designing and deploying production-grade cloud applications.
  • Experience building front-end applications with React and TypeScript, and back-end services with Node.js or comparable application frameworks.
  • Hands-on experience building Generative AI and RAG applications with Azure AI Foundry, Azure OpenAI, Azure AI Search, LLM APIs, embeddings, vector or hybrid search, knowledge retrieval, grounding, and citations.
  • Experience with Agentic AI frameworks such as Microsoft Agent Framework, Semantic Kernel, LangGraph, AutoGen, or comparable orchestration frameworks; including single-agent and multi-agent systems, tool-calling workflows, and human-in-the-loop controls.
  • Experience evaluating and improving agent quality, including prompt engineering, test datasets, LLM-based evaluation, safety checks, and production feedback loops.
  • Strong knowledge of LLMOps, CI/CD, containerization (Docker and Kubernetes), observability, and production operations for AI applications.
  • Good understanding of RESTful API principles, asynchronous application patterns, secure integrations, relational databases, SQL, and data-access patterns; familiarity with SQL/NoSQL data stores and data engineering or ETL pipelines.

Experience working in an enterprise environment with large-scale, secure AI deployments, including identity, authorization, data privacy, compliance, and production monitoring.

Strong analytical, problem-solving, collaboration, and communication skills.
Must be a US Citizenship or Green card holder