Lead Software Engineer-AI Platform Engineer
Lead Software Engineer-AI Platform Engineer
Posted on :
17-09-2025
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1 Vacancy
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Job Description
Description
We have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible.
As a Lead Software Engineer at JPMorgan Chase within the Corporate Sector specifically as a part of the Infrastructure Platforms team you will play a crucial role in an agile team committed to enhancing creating and delivering high-quality technology products in a secure stable and scalable manner. Your role as a vital technical contributor will involve developing critical technology solutions across numerous technical domains within various business functions all aimed at supporting the firms business goals.
Job Responsibilities:
- Execute creative software solutions including design development and technical troubleshooting with the ability to think beyond conventional approaches to build solutions or resolve technical problems.
- Develop secure high-quality production code and review and debug code written by others.
- Identify opportunities to eliminate or automate the remediation of recurring issues to enhance the overall operational stability of software applications and systems.
- Lead evaluation sessions with external vendors startups and internal teams to drive outcomes-oriented assessments of architectural designs technical credentials and their applicability within existing systems and information architecture.
- Lead communities of practice across Software Engineering to promote awareness and adoption of new and leading-edge technologies.
- Contribute to a team culture of diversity equity inclusion and respect.
- Develop and deploy cloud infrastructure platforms that are secure scalable and optimized for AI and machine learning workloads.
- Collaborate with AI teams to understand computational needs and translate these into infrastructure requirements.
- Monitor manage and optimize cloud resources to maximize performance and minimize costs.
- Design and implement continuous integration and delivery pipelines for machine learning workloads.
- Develop automation scripts and infrastructure as code to streamline deployment and management tasks.
Required Qualifications Capabilities and Skills:
- Formal training or certification in software engineering concepts with 5 years of applied experience.
- Hands-on practical experience in delivering system design application development testing and ensuring operational stability.
- Proficiency in at least one programming language such as Python Go Java or C#.
- Proficiency in automation and continuous delivery methods.
- Proficient in all aspects of the Software Development Life Cycle.
- Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g. cloud artificial intelligence machine learning mobile etc.).
- Foundational understanding of machine learning concepts including transformer architecture ML training and inference.
- Experience in solutions design and engineering containerization (Docker Kubernetes) and cloud service providers (AWS Azure GCP).
- Experience with Infrastructure as Code.
- Deep understanding of cloud component architecture: Microservices Containers IaaS Storage Security and routing/switching technologies.
Preferred qualifications capabilities and skills
- Foundational understanding of NVIDIA GPU infrastructure software (e.g. DCGM BCM Triton Inference).
- Hands-on experience with machine learning frameworks such as PyTorch and TensorBoard.
- Proficiency with observability tools like Prometheus and Grafana.
- Experience in ML Ops and related tooling including MLflow.
- Background in high performance computing and ML frameworks (e.g. vLLM Slurm).
- Strong knowledge of network architecture database programming (SQL/NoSQL) and data modeling.
- Familiarity with cloud data services big data processing tools and Linux environments (scripting and administration).
Employment Type
Full-Time
Key Skills
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