Live opening · Posted 1 day ago
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Job Description
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.
Required Skills & Experience
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.
(ref:hirist.tech)
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