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Tech Stack
Tools & technologiesAWSAzureCloud
About the role
Key responsibilities & impact- Designs, develops, tests, and maintains scalable software, machine learning, and agentic AI platform solutions within a defined technical domain.
- Builds and supports multi-tenant ML and agentic platforms using established engineering and MLOps practices.
- Delivers reliable, secure, and high-quality solutions while collaborating with cross-functional teams to execute well-scoped initiatives and enhance platform capabilities.
- Implements well-scoped features and enhancements using established coding standards, architectural patterns, and development best practices.
- Contributes to the reliability, scalability, and performance of applications by writing high-quality, maintainable code and participating in peer code reviews.
- Troubleshoots, debugs, and resolves software defects and production issues within area of responsibility, applying root-cause analysis as needed.
- Participates in the full software development lifecycle, including requirements refinement, design discussions, development, testing, deployment, and support.
- Applies secure coding practices, testing strategies, and documentation standards to ensure software quality and compliance with team guidelines.
Requirements
What you’ll need- Bachelor’s degree and 3 years of experience or equivalent education and software engineering training or experience.
- In-depth knowledge of information systems with the ability to identify, apply, and implement IT best practices.
- Understanding of key business processes and competitive strategies related to the IT function.
- Bachelor’s degree in computer science, computer engineering, or related field with eight years of experience, or equivalent combination of education and work experience.
- Strong foundation in software engineering, including data structures, algorithms, system design, and enterprise application development, with experience scaling solutions from concept to production.
- Experience designing and developing multi-tenant platforms with capabilities for tenant isolation, governance, scalability, and support for multiple teams and use cases.
- Hands-on experience with ML platform components, including feature stores, model training pipelines, model registry, inference services, and monitoring frameworks.
- Proven experience with MLOps and platform engineering practices, including CI/CD for ML, automated deployment, lifecycle management, and reproducibility.
- Experience building scalable, secure, and cost-efficient cloud-based platforms (e.g., Azure, AWS), including architecture patterns for multi-tenant deployments.
- Experience designing and implementing agentic AI platforms or frameworks, including agent orchestration, multi-agent workflows, tool integration (APIs, retrieval systems), and memory/reasoning patterns using LLMs is a plus.
- Knowledge of governance, security, and responsible AI practices, including data/model governance, regulatory considerations (especially in financial services), and controls for monitoring, auditability, and safe AI adoption is a plus.
Benefits
Comp & perks- Medical, dental, vision, life insurance
- Disability, accidental death and dismemberment
- Tax-preferred savings accounts
- 401k plan
- No less than 10 days of vacation (prorated based on date of hire and by full-time or part-time status)
- 10 sick days (also prorated)
- Paid holidays.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
software developmentmachine learningMLOpscoding standardsroot-cause analysisdata structuresalgorithmssystem designenterprise application developmentagentic AI
Soft Skills
collaborationproblem-solvingcommunicationteamworkattention to detailadaptabilitycritical thinkingtime managementorganizational skillsleadership