Lead Software Engineer Jobs in Seattle, WA
Lead Software Engineer jobs in Seattle are in strong demand, concentrated in South Lake Union, Capitol Hill, and Bellevue across cloud infrastructure, enterprise software, and consumer technology. Employers hiring right now include JPMorganChase, Blue Origin, and Amazon Web Services. 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 Seattle
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Find Lead Software Engineer JobsLead Software Engineer Job Market in Seattle
Who's Hiring
Top Industries Hiring
- Technology & Software12
- Distribution & Wholesale1
- Construction & Real Estate1
- Banking & Financial Services1
Lead Software Engineer Jobs in Seattle: Frequently Asked Questions
How do I get a lead software engineer job in Seattle?
Target Seattle's densest hiring corridors: South Lake Union's cloud and platform companies, Bellevue's enterprise software firms, and the growing fintech and healthtech clusters throughout the metro. Candidates who demonstrate distributed systems experience, prior team leadership, and a portfolio of shipped features at scale stand out. Engaging Seattle's active engineering meetup community and contributing to open-source projects with local collaborators also builds visibility with hiring managers here.
Which companies hire lead software engineers in Seattle?
Employers hiring lead software engineers in Seattle right now include JPMorganChase, Blue Origin, and Amazon Web Services, based on current listings on Migrate Mate as of September 2026. Seattle's hiring mix includes global technology giants, mid-stage venture-backed startups, and established enterprise software companies, many headquartered or with major engineering offices in the South Lake Union and Eastside corridors.
Are there remote lead software engineer jobs in Seattle?
Yes, though many lead software engineer roles require on-site collaboration given the team leadership and architecture review responsibilities the position carries. About 67% of lead software engineer openings tied to Seattle are remote or hybrid as of September 2026, with fully remote options most common in platform engineering and backend infrastructure teams at Seattle-area cloud companies.
How can I get a lead software engineer job in Seattle with little or no experience?
The most realistic entry path is targeting senior software engineer roles at Seattle's mid-size startups in South Lake Union or Eastside tech hubs, where informal leadership opportunities arise faster than at larger companies. Seek out roles that include mentorship responsibilities or tech lead components, and pursue on-call rotation ownership to build the incident response experience Seattle employers expect before promoting into a formal lead title.
Which industries hire the most lead software engineers in Seattle?
Seattle lead software engineer roles concentrate in Technology & Software, Distribution & Wholesale, and Construction & Real Estate, based on current listings on Migrate Mate as of September 2026. Seattle's position as a global cloud computing hub, combined with a maturing healthtech sector and longstanding aerospace and defense presence, keeps engineering leadership demand consistently high across these verticals.
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See All 51 Lead Software Engineer Jobs in Seattle
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