AI/Python Developer
Role details
Job location
Tech stack
Job description
- Build and deploy production-ready AI-powered services using LLMs and Generative AI.
- Develop and enhance components for RAG pipelines, agentic workflows, and knowledge-grounded reasoning systems.
- Write high-quality, testable, and maintainable Python code with a strong focus on observability, reliability, and performance.
- Design and implement scalable, cloud-native services and distributed systems for AI-powered applications.
- Own key service-level components across APIs, microservices, data pipelines, and vector-backed retrieval systems.
- Partner with product, platform, and data teams to integrate AI capabilities into business applications.
- Contribute to technical design discussions and help drive implementation for complex feature areas.
- Participate actively in code reviews, design reviews, and operational improvements to raise engineering quality.
Requirements
We are seeking curious, outcome-focused engineers with a product mindset for a high-visibility initiative. This role involves building and deploying production-ready, AI-powered services using Large Language Models (LLMs) and Generative AI. The ideal candidate will focus on delivering tangible results and will have their work evaluated based on solving practical, real-world problems., Experience: 5+ years of experience in software engineering, with strong experience in backend systems, distributed systems, or cloud platforms. Candidates should have hands-on experience with Generative AI and LLM-based applications in production settings and a track record of delivering production-quality software.
Technical Skills: Strong coding skills in Python and experience building production-grade backend systems are required. This includes experience with scalable microservices, APIs, and event-driven systems. Familiarity with vector databases, RAG pipelines, and LLM integration patterns is also necessary.
Preferred Qualifications
- Experience with cloud platforms such as Azure, Google Cloud Platform, or AWS.
- Experience with observability, monitoring, and production operations for AI-powered systems.
- Exposure to AI/ML frameworks such as PyTorch, TensorFlow, or Hugging Face.
- Familiarity with security, compliance, and responsible AI considerations in enterprise environments.
Work Environment
This role requires onsite presence 3-4 days per week. Relocation assistance may be considered for candidates moving to the work location.