Sobre este puesto de Senior AI Engineer en Weekday AI
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฐ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฑ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฐ๐ฌ-๐ฑ๐ฑ ๐๐ฃ๐)
Experience: 5+ yrs
Location: Bengaluru, Karnataka, India
Job Type: Full-time
We are looking for an experiencedย Senior AI Engineerย with strong expertise inย Python, Rust, backend engineering, and production-grade AI systemsย to build and scale intelligent applications and AI-powered platforms. The ideal candidate will combine solid software engineering fundamentals with hands-on experience developing LLM-powered applications, AI agents, and scalable backend services.
You will play a key role in transforming AI capabilities into reliable production systems, focusing on performance, scalability, observability, and maintainability. This position is suited to an engineer who enjoys solving complex technical challenges, taking ownership of end-to-end delivery, and exploring modern AI technologies.
Requirements
Key Responsibilities
- Design, build, and maintain production-grade AI applications and backend services usingย Python and Rust.
- Develop and deploy LLM-powered applications, intelligent assistants, AI agents, and automated workflows.
- Implementย tool-calling, RAG pipelines, embeddings, vector search, and agent orchestrationย capabilities.
- Build scalable APIs, asynchronous processing systems, database integrations, and reusable backend components.
- Integrate external model APIs, inference services, and model-serving infrastructure into production applications.
- Evaluate model and application performance, including response quality, latency, reliability, and resource utilisation.
- Design robust service architectures with appropriate error handling, retries, security, and fault tolerance.
- Deploy and manage services usingย Docker, Kubernetes, cloud infrastructure, and CI/CD pipelines.
- Implement observability through structured logging, metrics, distributed tracing, dashboards, and alerts.
- Troubleshoot production issues, conduct root-cause analysis, and drive continuous performance improvements.
- Take ownership of engineering capabilities from technical design and implementation through deployment and ongoing operations.
- Collaborate with product and engineering stakeholders to translate requirements into practical technical solutions.
- Contribute to code reviews, architecture discussions, engineering standards, and technical documentation.
- Explore emerging AI techniques and contribute to the evolution of a Rust-based AI platform.
What Makes You a Great Fit
- 5+ years of professional software engineering experience, with strong proficiency in Python and/or Rust.
- Hands-on experience building and deployingย LLM-powered applications, AI agents, or production AI systems.
- Strong understanding of RAG, embeddings, vector databases, semantic search, tool-calling, and agent workflows.
- Solid backend engineering fundamentals, including API design, asynchronous processing, databases, and service architecture.
- Production experience with Docker, Kubernetes, cloud platforms, and automated CI/CD workflows.
- Familiarity with observability tools and practices involving logs, metrics, traces, and alerts.
- Understanding of model APIs, inference pipelines, and model-serving infrastructure.
- Strong debugging, problem-solving, and performance-optimisation skills.
- Ability to independently own complex technical initiatives from concept through production.
- Excellent written and verbal communication skills, with the ability to clearly explain technical gaps, risks, and trade-offs.
- Interest in learning Rust and contributing to a Rust-based platform.
- A strong ownership mindset and commitment to building reliable, scalable, secure, and maintainable AI systems.