Senior Software Engineer
About The Position
In this role, you will design and build scalable backend systems, cloud infrastructure, and platform capabilities that power AI/ML products and applications. You will partner closely with AI/ML engineers, data scientists, and cross-functional teams to productionize LLM applications, RAG pipelines, and agentic AI workflows. You will leverage modern cloud technologies, infrastructure-as-code practices, and AI-assisted development tools to deliver reliable, secure, and maintainable solutions that accelerate innovation across the AI/ML team while helping establish engineering standards, reusable platform patterns, and operational best practices.
Requirements
- Relevant degree preferred.
- 5 or more years of relevant experience required.
- Strong Python development experience with expertise building production backend services, APIs, distributed systems, and cloud-based applications required.
- Hands-on experience with Pulumi, Terraform, or other infrastructure-as-code tools along with cloud platforms such as AWS, Azure, or GCP required.
- Knowledge of observability tools, monitoring, logging, tracing, alerting frameworks, and production support practices.
- Strong analytical, troubleshooting, problem-solving, verbal communication, and written communication skills with the ability to collaborate across technical and business teams.
- Ability to operate effectively in fast-paced, evolving environments with a high level of ownership, accountability, and adaptability.
Nice To Haves
- Experience with Docker, CI/CD pipelines, infrastructure automation, container orchestration, Kubernetes, serverless architectures, and cloud deployment practices preferred.
- Familiarity with ML/AI systems, model serving, LLM applications, inference pipelines, RAG workflows, data pipelines, or related AI platform technologies.
- Experience with Databricks, Azure AI Foundry, or similar AI/ML platform technologies preferred.
Responsibilities
- Design, develop, and maintain backend services, APIs, and platform components that support AI/ML applications and distributed systems.
- Build scalable cloud infrastructure using Pulumi and modern infrastructure-as-code practices while developing CI/CD pipelines, deployment workflows, and containerized cloud environments.
- Support production deployment of ML models, LLM applications, RAG pipelines, and agentic AI systems while collaborating with AI/ML engineers to productionize model serving, inference pipelines, and data workflows.
- Enhance observability through monitoring, logging, tracing, alerting, and incident management practices to improve operational reliability and system performance.
- Implement engineering standards for testing, code quality, security, maintainability, scalability, latency optimization, and cost efficiency.
- Define reusable platform patterns, developer tooling, and engineering workflows that improve developer productivity and operational consistency across the AI/ML team.
- Evaluate emerging AI engineering trends, AI-assisted development tools, and modern software practices to drive continuous improvement and innovation.
- Partner with product, security, data, and platform teams to deliver production-ready AI solutions while contributing to architectural discussions and long-term platform strategy.
- Troubleshoot complex production issues, perform root cause analysis, and drive remediation efforts to improve system stability and reliability.
- Mentor engineers through technical collaboration, code reviews, knowledge sharing, and engineering best practices.
Benefits
- Comprehensive benefits plan
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
