Job Description
We are seeking a highly skilled Data Scientist to help build and lead a team focused on Generative AI and data science enablement. This role will work closely with data scientists to design and deliver scalable AI-powered systems, particularly around Retrieval-Augmented Generation (RAG), LLM-based solutions, and NLP-driven applications.
The ideal candidate combines strong Python engineering expertise, experience delivering customer-facing products, and the ability to architect solutions for complex AI-driven environments. This role will also involve mentoring junior engineers and supporting production-grade AI services.
- Must Have Qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field (Master’s or PhD preferred)
- 4+ years of software engineering experience, particularly collaborating with data science or AI teams
- Hands-on experience with Generative AI systems, including LLMs, NLP pipelines, and RAG implementations
- Proven experience building and deploying end-to-end customer-facing software products
- Strong proficiency in Python and modern backend development practices
- Experience designing architecture and scalable solutions for AI-driven applications
- Ability to mentor and guide junior engineers
- Strong problem-solving and system design skills
- Preferred Qualifications
- Previous experience working at large technology companies or comparable organizations, such as Amazon, Meta, Microsoft, Apple, Thomson Reuters, or similar environments
- Exposure to large-scale distributed systems or AI platforms
- Experience working closely with data scientists, ML engineers, and product teams
Key Responsibilities
- Technical Leadership
- Design and develop scalable software architectures supporting generative AI and machine learning workflows
- Lead the development of Python-based services, APIs, libraries, and microservices
- Support RAG pipelines, LLM integrations, and NLP-based systems
- Collaboration
- Work closely with data scientists, product managers, and engineering teams to translate business requirements into technical solutions
- Collaborate across teams to deliver AI-powered features and services
- Development & Quality
- Implement high-quality, maintainable, and well-tested code
- Conduct code reviews and enforce engineering best practices
- Contribute to automated testing strategies including unit, integration, and end-to-end tests
- Team Leadership
- Help build and lead a team of engineers supporting AI initiatives
- Mentor junior engineers and promote knowledge sharing and continuous improvement
- Operations & Delivery
- Support regular service releases, monitoring, and issue resolution
- Maintain system reliability through service tracking, logging, and monitoring
- Continuous Improvement
- Stay current with emerging technologies in Python development, AI infrastructure, and generative AI ecosystems
- Recommend improvements in architecture, tooling, and engineering practices
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