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Senior Implementation Engineer Jobs in Redmond, WA

Saransh Inc

Senior AI Engineer - Privacy

Bellevue, WA · On-site

$117K - $162K/yr

Senior AI Engineer - Privacy Location: Bellevue, WA (Onsite from Day 1) Job Type: Contract Must ... Implement structured prompting, decision workflows, and tool orchestration -- including MCP (Model ...

DocuSign

Senior Software Engineer

Seattle, WA · On-site +1

$139K - $183K/yr

What you'll do Docusign is looking for a Senior Software Engineer to join our microservices ... Design, implement, and operate Microservice storage services that support Docusign's global ...

Docusign

Senior Software Engineer

Seattle, WA · On-site

$139K - $183K/yr

What you'll do Docusign is looking for a Senior Software Engineer to join our microservices ... Design, implement, and operate Microservice storage services that support Docusign's global ...

Stanley 1913

Senior Packaging Engineer

Seattle, WA · Hybrid

We are seeking a Senior Packaging Structural Engineer to join our Packaging Engineering team ... In this role, you will lead the design, development, and implementation of innovative structural ...

Stanley 1913

Senior Packaging Engineer

Seattle, WA · On-site

We are seeking a Senior Packaging Structural Engineer to join our Packaging Engineering team ... In this role, you will lead the design, development, and implementation of innovative structural ...

Comtech, LLC

Sr. Network Engineer

Seattle, WA

$118K - $162K/yr

The Senior Network Engineer position engages in network operations activities and facilitates ... Contributes to the formulation and implementation of installation standards and procedures.

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All JobsImplementation Engineer JobsSenior Implementation Engineer JobsSenior Implementation Engineer Jobs in Redmond, WA

Senior Implementation Engineer information

See Redmond, WA salary details

$30

$57

$90

How much do senior implementation engineer jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for senior implementation engineer in Redmond, WA is $57.57, according to ZipRecruiter salary data. Most workers in this role earn between $43.08 and $68.37 per hour, depending on experience, location, and employer.

What is a senior implementation engineer?

Senior Implementation Engineers are experienced professionals responsible for overseeing the deployment and integration of complex software, hardware, or IT systems for clients or within organizations. They work closely with project managers, clients, and technical teams to ensure solutions are delivered on time, meet requirements, and function as intended. Their role often includes designing implementation plans, troubleshooting issues, providing technical support, and training end-users. Senior Implementation Engineers typically bring several years of experience and deep technical expertise, enabling them to guide projects from initial planning to successful completion.

What are some common challenges faced by senior implementation engineers during large-scale software deployments?

Senior Implementation Engineers often encounter challenges such as managing complex integrations with existing client systems, coordinating cross-functional teams to meet tight deadlines, and troubleshooting unexpected technical issues during deployment. Communication is key, as these engineers frequently serve as the primary liaison between clients, internal developers, and project managers. Staying organized and adapting quickly to changing requirements are essential skills for overcoming these hurdles and ensuring successful project delivery.

What are the key skills and qualifications needed to thrive as a senior implementation engineer, and why are they important?

To thrive as a Senior Implementation Engineer, you need advanced technical expertise in systems integration, project management experience, and a strong background in computer science or a related field. Familiarity with enterprise software platforms, APIs, cloud services, and certifications like PMP or relevant vendor credentials are typically required. Excellent problem-solving abilities, communication skills, and the ability to lead cross-functional teams distinguish top performers. These capabilities are crucial for successfully deploying complex solutions, ensuring client satisfaction, and driving project success in dynamic environments.

What is the difference between Senior Implementation Engineer vs Implementation Engineer?

AspectSenior Implementation EngineerImplementation Engineer
Required CredentialsBachelor's degree in engineering or related field; often some certificationsBachelor's degree in engineering or related field; certifications are common
Work EnvironmentLead projects, mentor junior staff, coordinate with clientsAssist in deploying solutions, support implementation teams
Employer & Industry UsageTechnology, software, telecommunications companiesTechnology, software, telecommunications companies

The main difference is experience level and responsibilities. Senior Implementation Engineers typically lead projects and mentor others, while Implementation Engineers focus on executing deployment tasks. Both roles require similar credentials and are used in comparable industries.

What cities near Redmond, WA are hiring for Senior Implementation Engineer jobs?

Cities near Redmond, WA with the most Senior Implementation Engineer job openings:

Senior Implementation Engineer jobs near you
Infographic showing various Senior Implementation Engineer job openings in Redmond, WA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, and 5% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $125,973 per year, or $60.6 per hour.

Senior AI Engineer - Privacy

Bellevue, WA • On-site

Saransh Inc
IT Services • 51 - 200 employees
Learn more about Saransh Incexternal

$117K - $162K/yr

Contractor

Re-posted 11 days ago

Job description

Role: Senior AI Engineer – Privacy
Location: Bellevue, WA (Onsite from Day 1)
Job Type: Contract
 
Must Have Skills:
  • 7 yrs of exp – AI Engineer – Privacy
  • 7 yrs of exp – Azure Data Factory, Azure , GitLab
  • 5 yrs of exp – Databricks, Snowflake
Description:
  • The Senior AI Engineer – Privacy will design, build, and operationalize AI and agentic systems that power Client data privacy platform at scale.
  • Embedded within the Data & Intelligence organization's Privacy practice, this engineer will apply large language models (LLMs), retrieval-augmented generation (RAG), multi-agent orchestration, and foundation model capabilities to automate, enhance, and scale privacy operations — including Data Subject Request (DSR) processing, consent management, regulatory compliance monitoring, and privacy impact assessment workflows — across a customer base of over 100 million.

AI Agent & LLM Engineering
• Design and build multi-agent systems, orchestration layers, and agentic workflows using frameworks such as LangChain, LangGraph, Google ADK, or equivalent.
• Develop and operationalize RAG (Retrieval-Augmented Generation) pipelines integrating LLMs (e.g. Claude, Gemini, GPT-4) into production privacy applications.
• Implement structured prompting, decision workflows, and tool orchestration — including MCP (Model Context Protocol)-based architectures — for autonomous agent systems.
• Build AI-powered automation for privacy operations including intelligent DSR routing, threshold monitoring, agentic data quality checks, and automated regulatory notifications.
• Enable human-in-the-loop controls and escalation paths for AI-assisted decisions in sensitive privacy workflows.
Data & ML Engineering
• Build and optimize data pipelines using Azure Data Factory, Databricks, Snowflake, or PySpark to support AI model training, fine-tuning, and inference.
• Apply prompt engineering, few-shot learning, and fine-tuning techniques to adapt foundation models for privacy-specific use cases.
• Implement vector databases and embedding strategies to power RAG pipelines over Client internal privacy knowledge bases and policy documents.
• Ensure data quality, lineage, and governance standards are maintained across all AI training and inference pipelines.
Cloud & MLOps
• Deploy and manage AI workloads on Azure or AWS, including serverless inference endpoints, container registries, and GPU/compute resources.
• Build and maintain CI/CD pipelines for AI model deployment using GitLab or Azure DevOps, applying MLOps best practices.
• Implement monitoring, alerting, and performance tracking for production AI models and agent systems using Splunk, AppDynamics, or Grafana.
• Apply containerization (Docker) and orchestration (Kubernetes) to ensure scalable and reliable AI service deployments.
Responsible AI & Compliance
• Implement responsible AI principles — including fairness, transparency, and explainability — across all AI systems used in privacy operations.
• Ensure AI-assisted workflows comply with CCPA, CPRA, TCPA, and other applicable state and federal privacy regulations.
• Design and maintain audit trails and human-in-the-loop checkpoints for AI decisions affecting consumer privacy rights.
• Collaborate with legal, compliance, and privacy operations teams to translate regulatory requirements into AI solution guardrails and constraints.
Technical Leadership & Collaboration
• Partner with data engineers, full stack engineers, product managers, and privacy stakeholders to deliver end-to-end AI-powered privacy solutions.
• Mentor junior engineers on AI/ML engineering practices, agentic patterns, and responsible AI design principles.
• Produce clear technical documentation, architecture diagrams, and model cards for AI systems in production.
• Contribute to internal accelerators, reusable AI component libraries, and the broader engineering community of practice.