Lead Software Engineer Jobs in Washington
Lead Software Engineer jobs in Washington are among the most active in the country, concentrated in cloud infrastructure, enterprise software, and applied machine learning across the full range from mid-level to staff and principal. Seattle and Bellevue anchor the market, with Redmond close behind, and employers like Microsoft, Amazon, and Boeing consistently post lead-level openings across product, platform, and aerospace software teams. The most in-demand specialties right now are distributed systems, developer tooling, and AI-adjacent backend engineering. Find a role that fits below and apply directly.
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Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Sector, Infrastructure Platforms team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job Responsibilities
- Provide technical guidance aligned to business goals, collaborating with engineers, contractors, and vendors.
- Develop secure, high-quality production code; review, debug, and improve others' code.
- Influence product design, application functionality, and technical operations through informed decisions.
- Champion firmwide SDLC frameworks, tools, and best practices.
- Promote a culture of diversity, Opportunity, inclusion, and respect.
- Architect and deploy secure, scalable cloud platforms optimized for AI/ML workloads.
- Partner with AI teams to translate compute needs into infrastructure requirements.
- Monitor, manage, and optimize cloud resources for performance and cost efficiency.
- Build CI/CD, automation, and infrastructure-as-code to streamline ML deployment and operations.
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on experience in system design, application development, testing, and operational stability.
- Strong experience with Kubernetes and containerization (Docker), including cluster operations and production troubleshooting.
- Proficiency in at least one programming language, such as Python, Go, Java, or C#.
- Ability to independently tackle design and functionality problems with minimal oversight.
- Strong knowledge of cloud computing delivery models (IaaS, PaaS, SaaS) and deployment models (Public, Private, Hybrid Cloud).
- Foundational understanding of machine learning concepts, including transformer architecture, ML training, and inference.
- Experience with Infrastructure as Code.
- Deep understanding of cloud component architecture: Microservices, IaaS, Storage, Security, and routing/switching technologies.
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
Preferred qualifications, capabilities, and skills
- Foundational understanding of NVIDIA GPU infrastructure software (e.g., DCGM, BCM, Dynamo Inference).
- Proficiency with observability tools like Prometheus and Grafana.
- Experience in ML Ops and related tooling, including MLflow.
- Experience building and scaling a high-performance LLM inference platform—leveraging vLLM and GPU/CPU serving optimization—to deliver low-latency, high-throughput, production-grade model serving.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Sector, Infrastructure Platforms team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job Responsibilities
- Provide technical guidance aligned to business goals, collaborating with engineers, contractors, and vendors.
- Develop secure, high-quality production code; review, debug, and improve others' code.
- Influence product design, application functionality, and technical operations through informed decisions.
- Champion firmwide SDLC frameworks, tools, and best practices.
- Promote a culture of diversity, Opportunity, inclusion, and respect.
- Architect and deploy secure, scalable cloud platforms optimized for AI/ML workloads.
- Partner with AI teams to translate compute needs into infrastructure requirements.
- Monitor, manage, and optimize cloud resources for performance and cost efficiency.
- Build CI/CD, automation, and infrastructure-as-code to streamline ML deployment and operations.
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on experience in system design, application development, testing, and operational stability.
- Strong experience with Kubernetes and containerization (Docker), including cluster operations and production troubleshooting.
- Proficiency in at least one programming language, such as Python, Go, Java, or C#.
- Ability to independently tackle design and functionality problems with minimal oversight.
- Strong knowledge of cloud computing delivery models (IaaS, PaaS, SaaS) and deployment models (Public, Private, Hybrid Cloud).
- Foundational understanding of machine learning concepts, including transformer architecture, ML training, and inference.
- Experience with Infrastructure as Code.
- Deep understanding of cloud component architecture: Microservices, IaaS, Storage, Security, and routing/switching technologies.
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
Preferred qualifications, capabilities, and skills
- Foundational understanding of NVIDIA GPU infrastructure software (e.g., DCGM, BCM, Dynamo Inference).
- Proficiency with observability tools like Prometheus and Grafana.
- Experience in ML Ops and related tooling, including MLflow.
- Experience building and scaling a high-performance LLM inference platform—leveraging vLLM and GPU/CPU serving optimization—to deliver low-latency, high-throughput, production-grade model serving.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
See All 51 Lead Software Engineer Jobs in Washington
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Find Lead Software Engineer JobsLead Software Engineer Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
Lead Software Engineer Job Market in Washington
A snapshot from current Washington openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Distribution & Wholesale
- Construction & Real Estate
- Banking & Financial Services
What Washington Employers Look For
The qualifications that appear most often in lead software engineer jobs across Washington.
- Bachelor's or master's degree in computer science, software engineering, or a related technical field
- Seven or more years of software engineering experience with at least two in a technical lead capacity
- Proficiency in one or more of Java, Python, C++, Go, or TypeScript in a production environment
- Demonstrated experience designing distributed systems or large-scale cloud-native architectures on AWS, Azure, or GCP
- Experience mentoring engineers and driving technical direction across cross-functional product teams
- Strong background in agile delivery, code review culture, and engineering best practices including CI/CD pipelines
Lead Software Engineer Jobs in Washington: Frequently Asked Questions
How do you become a lead software engineer in Washington?
Lead software engineers in Washington are not licensed by the state, so there is no board exam or registration required. The typical path is a computer science or software engineering degree followed by several years as an individual contributor, then a move into a senior role at one of Washington's large technology employers or a mid-size product company before stepping into a lead position. Strong distributed systems experience and a record of mentoring junior engineers are what Washington hiring managers weigh most.
How much do lead software engineers make in Washington?
Lead software engineers in Washington earn a median of about $166,540 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $96,810 for the lowest 10% to over $255,350 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire lead software engineers in Washington?
Employers hiring lead software engineers in Washington right now include Amazon, JPMorganChase, and Blue Origin, based on current listings on Migrate Mate as of September 2026. Washington's density of major technology headquarters and aerospace operations means lead-level engineering roles open frequently and tend to require deep platform or systems experience rather than purely product-focused backgrounds.
Which Washington cities have the most lead software engineer jobs?
Seattle, Redmond, and Kent have the most lead software engineer openings in Washington. Seattle and Bellevue dominate because they are home to the headquarters and major campuses of the state's largest technology employers, while Redmond's concentration of Microsoft operations and nearby Kirkland's growing product engineering scene push consistent demand outside the core Seattle corridor.
Are there remote lead software engineer jobs in Washington?
Yes, and more than most fields. About 67% of lead software engineer openings tied to Washington are remote or hybrid as of September 2026, reflecting how naturally the work translates to distributed collaboration. Architecture reviews, code reviews, and cross-team technical coordination are the parts of the role most commonly performed fully remotely, while teams that own on-call infrastructure or embedded hardware components tend to require more in-person presence.
How can I get hired as a lead software engineer in Washington with little or no experience?
The most realistic entry path is through an associate or junior software engineering role at one of Washington's large technology companies, which run structured new-graduate programs that move engineers toward senior and lead tracks. Microsoft's Garage and Amazon's engineering development rotations are examples of programs that develop engineers from the ground up. Building a strong portfolio of distributed systems or cloud projects and contributing to open-source repositories that Washington employers actively use can accelerate that progression significantly.
Where can I find and apply to lead software engineer jobs in Washington?
You can find and apply to lead software engineer jobs in Washington on Migrate Mate, which lists current Washington openings. Find roles that fit your background and apply directly from the listing.
See All 51 Lead Software Engineer Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
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