AI/ML Computational Science Sr Analyst
Mentions vibe-coding and AI-assisted tools (GitHub Copilot, Kiro) and expects familiarity with LLMs, LangChain and prompt engineering.
About the Role
Senior Analyst role focused on Python-based development and AI/ML integration, responsible for designing, building, testing, and deploying scalable backend services and APIs. The role also involves working with generative AI tools (LLMs, LangChain, OpenAI, Hugging Face), cloud platforms, and contributing as a domain SME in solution design and delivery.
Job Description
Role
AI/ML Computational Science Senior Analyst (Python Developer) responsible for designing, developing, testing, and deploying scalable Python applications and services, building RESTful APIs and microservices, and integrating AI/ML components. The position expects independent contribution, participation in architecture and design discussions, and becoming a subject-matter expert in the assigned domain.
Key Responsibilities
- Design, develop, and maintain enterprise-grade applications using Python.
- Build scalable RESTful APIs and microservices; integrate third-party APIs.
- Develop and optimize backend services for performance and reliability.
- Participate in solution design, code reviews, testing, and deployment activities.
- Troubleshoot application issues and provide timely resolutions.
- Create and maintain technical documentation, workflows, and user guides.
- Follow software development best practices, coding standards, and security guidelines.
- Contribute to Agile delivery processes, continuous improvement, and delivery success.
- Mentor junior developers and support knowledge-sharing initiatives.
Requirements
- Education: Bachelor’s degree (Computer Science, Engineering, IT, or related discipline) or equivalent.
- Experience: Posting contains conflicting experience requirements (listed as 3 years in some places and 5+ years of Python development experience in the core Python section).
- Strong proficiency in Python and Object-Oriented Programming; familiarity with design patterns and software engineering principles.
- Experience with Python frameworks such as Django, FastAPI, or Flask.
- RESTful API development and microservices architecture experience.
- Database experience: SQL (PostgreSQL, MySQL, SQL Server) and NoSQL (MongoDB, DynamoDB); database design and optimization.
- Version control (Git) and DevOps practices including CI/CD pipelines, Docker; Kubernetes preferred.
- Cloud platform experience (Azure, AWS, GCP).
- Testing and quality practices: unit and integration testing, debugging, and performance optimization.
- Strong analytical, communication, stakeholder management, and collaboration skills; ability to work independently.
- Exposure to Generative AI concepts: LLMs, prompt engineering, RAG, embeddings, vector databases; familiarity with agentic AI architectures.
- Experience with AI/ML tools and libraries such as LangChain, OpenAI APIs, Hugging Face, LangGraph; exposure to Pandas, NumPy, Scikit-Learn.
Preferred / Good to Have
- Experience with GitHub Copilot, Kiro, or other AI-assisted development tools.
- Prior vibe-coding experience or rapid prototyping with AI tools.
- Experience deploying and monitoring AI applications.