How does swipeandhired work?

You set your target roles, salary floor and locations once. swipeandhired scores matching postings against your profile, drafts tailored application materials with AI, and either lets you swipe to apply, one tap at a time, or runs fully on autopilot. Every application is tracked in your dashboard.

Which ATS platforms does swipeandhired support?

All of them. swipeandhired applies on every applicant tracking system (ATS) employers use, including Workday, SmartRecruiters, Greenhouse, iCIMS, Lever, Ashby, Taleo, SuccessFactors, Oracle Cloud and Jobvite, and on a company's own careers page when it uses none of them. You can also bring any posting yourself by link or pasted text.

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Anytime, in one click from the billing portal in Settings. Your plan stays active until the end of the current billing period. No retention calls, no dark patterns.

Is my data used for training AI models?

No. Your resume and application data are processed only to run the service for you, matching, drafting, and submitting applications. We never sell your data. If you bring your own AI provider key, requests go directly to your provider under their terms.

Lead Software Engineer - Agentic AI at JPMorgan Chase, Jersey City, NJ

Lead Software Engineer - Agentic AI at JPMorgan Chase in Jersey City, NJ. Est. up to $200k. Apply with swipeandhired.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase with in Enterprise Technology Cloud Foundational Services, 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. As a core technical contributor, you are responsible for delivering critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Job Responsibilities

Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build solutions or break down technical problems.

Deliver end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.

Design, develop, and deploy resilient, fault-tolerant applications on AWS, leveraging services such as ECS, EKS, Lambda, RDS, S3, and API Gateway to ensure high availability and operational excellence.

Provision, manage, and maintain cloud infrastructure using Terraform, enforcing infrastructure-as-code best practices, reusable module design, and consistent environment management across development, staging, and production.

Architect and build agentic AI applications using modern frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, or AWS Bedrock Agents), enabling autonomous, multi-step reasoning and tool-use capabilities within production-grade systems.

Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.

Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.

Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.

Promptly investigate and resolve issues, ensuring they do not resurface.

Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.

Required Qualifications, Capabilities, and Skills

Formal training or certification on software engineering concepts and 5+ years applied experience

Demonstrated experience leading effective use of approved AI-assisted software development tools (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 engineers on safe, compliant adoption within delivery practices

Proficiency in back-end technologies (e.g., Python, Flask, Django) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, TypeScript, React, Angular).

Strong hands-on experience developing and deploying resilient applications on AWS, including deep familiarity with core AWS services, high-availability design patterns, disaster recovery strategies, and AWS Well-Architected Framework principles.

Strong understanding and hands-on experience in cloud infrastructure provisioning using Terraform, including writing modular, reusable infrastructure-as-code, managing remote state, and integrating Terraform into CI/CD pipelines.

Hands-on experience building agentic AI applications using one or more frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, AWS Bedrock Agents), including designing multi-agent workflows, tool integrations, memory management, and orchestration patterns.

Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON.

Experience with agile development methodologies (e.g., Scrum) and an understanding of the software development life cycle..

Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.

Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).

Preferred Qualifications, Capabilities, and Skills

Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management.

Strong problem-solving, analytical, and communication skills.

Ability to drive broader impact by sharing and contributing best practices.

Experience in the banking domain.

AWS certification (e.g., AWS Certified Solutions Architect – Associate/Professional, AWS Certified DevOps Engineer, or AWS Certified Machine Learning – Specialty).

Experience with AWS CDK or CloudFormation as complementary infrastructure tooling alongside Terraform.

Familiarity with LLM evaluation frameworks, prompt engineering, and responsible AI practices in the context of agentic system design.