InfoBeans Technologies - AI/ML Developer - Generative AI/Agentic Frameworks
InfoBeans
We are looking for an experienced AI/ML Developer with strong hands-on expertise in Python, Generative AI, and agentic development. The role focuses on applying AI to software engineering and business workflows, building reusable agentic frameworks, and accelerating the adoption of AI-powered solutions in production. The ideal candidate should be comfortable working independently with client engineering leads to design, prototype, validate, and implement practical AI solutions.
Key Responsibilities
- Design and develop AI-powered agents for software development lifecycle (SDLC) workflows, including code generation, pull request reviews, testing, and engineering automation.
- Build and maintain reusable agentic frameworks, skills libraries, prompts, instructions, and implementation patterns.
- Implement AI-assisted engineering workflows to improve developer productivity, code quality, testing efficiency, and delivery processes.
- Evaluate and integrate GenAI models, agentic frameworks, and AI development tools based on business and engineering requirements.
- Apply spec-driven development practices using tools such as Claude Code and GitHub Copilot to translate requirements and specifications into working solutions.
- Develop and integrate applications using Python, APIs, and enterprise data sources.
- Support automation initiatives across Azure and Databricks Lakehouse environments, identifying opportunities where AI can provide measurable value.
- Work with Databricks and Snowflake to support data integration and AI-enabled workflows.
- Contribute to credit-risk AI extensions and related use cases as business requirements evolve.
- Collaborate directly with client engineering leads to understand requirements, shape solution approaches, and drive implementation independently.
- Validate prototypes for accuracy, reliability, scalability, security, and production readiness.
- Establish reusable development patterns, documentation, and best practices for agentic solutions and AI-assisted engineering.
- Apply sound engineering judgment to determine when AI, agents, conventional automation, or traditional software development is the most appropriate approach.
- 6 - 10 years of experience in AI/ML development, Python engineering, application development, or related software engineering roles.
- Strong hands-on proficiency in Python and application engineering fundamentals.
- Practical experience with Generative AI and agentic development, including building AI-powered workflows or applications.
- Good understanding of APIs, system integration, data integration, and application architecture.
- Experience with Git, CI/CD pipelines, and software development lifecycle practices.
- Familiarity with cloud architecture and hands-on exposure to Microsoft Azure.
- Experience with Databricks and/or Snowflake, preferably in data engineering, analytics, or Lakehouse-related use cases.
- Hands-on familiarity with Claude Code, GitHub Copilot, or similar AI-assisted development tools.
- Understanding of spec-driven development and the ability to translate specifications into implementable engineering solutions.
- Ability to work independently with client engineering leads and communicate technical solutions clearly.
- Strong problem-solving skills and sound judgment when evaluating the practical value, limitations, and risks of AI-based solutions.