Gen Ai Developer
Epsilon Solutions Ltd.
Experienced professional with strong Python development and Generative AI expertise, especially in prompt engineering.Key Responsibilities
Leverage GenAI to accelerate:
Requirement gathering and analysis.Design creation (HLD/LLD).Reverse engineering of existing applications.Lead and enable development teams to effectively use GenAI tools and frameworks.Reverse engineer application codebases (Python, Java, Angular, Mule) to auto-generate:Data flow and sequence diagrams.Propose API specifications.Apply Domain-Driven Design (DDD) patterns.Utilize Claude Code, GitHub Copilot, and similar tools for:Pull Request reviews.Automated test generation.Development, Code refactoring and optimization.Build and deploy AI agents using LangChain, LangGraph, integrated with enterprise APIs.Implement RAG (Retrieval-Augmented Generation) pipelines for knowledge-driven applications.Drive prompt engineering best practices and GenAI use case adoption across teams.Conduct workshops and training sessions for developers on GenAI tools and frameworks.Ensure security, compliance, and responsible AI usage in all GenAI implementations.Must-Have Skills
Strong proficiency in Python and microservice development.Hands-on experience with Claude Code, GitHub Copilot, and prompt engineering.Expertise in LangChain, LangGraph, LangFlow, and agent-based architectures.Solid understanding of software design principles, DDD, and cloud-native architectures.Experience building AI solutions integrated with enterprise APIs.Preferred Skills
Familiarity with AWS services (Bedrock, Lambda, S3, DynamoDB, Postgres/PGVector).Knowledge of containerization (Docker) and CI/CD pipelines.Experience with vector databases, embedding models, and LLM fine-tuning.Understanding of AI governance, bias mitigation, and responsible AI frameworks.Proficiency with FastAPI, LangChain, LangGraph, Bedrock, Anthropic APIs.Experience with observability tools for AI workflows.
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Leverage GenAI to accelerate:
Requirement gathering and analysis.Design creation (HLD/LLD).Reverse engineering of existing applications.Lead and enable development teams to effectively use GenAI tools and frameworks.Reverse engineer application codebases (Python, Java, Angular, Mule) to auto-generate:Data flow and sequence diagrams.Propose API specifications.Apply Domain-Driven Design (DDD) patterns.Utilize Claude Code, GitHub Copilot, and similar tools for:Pull Request reviews.Automated test generation.Development, Code refactoring and optimization.Build and deploy AI agents using LangChain, LangGraph, integrated with enterprise APIs.Implement RAG (Retrieval-Augmented Generation) pipelines for knowledge-driven applications.Drive prompt engineering best practices and GenAI use case adoption across teams.Conduct workshops and training sessions for developers on GenAI tools and frameworks.Ensure security, compliance, and responsible AI usage in all GenAI implementations.Must-Have Skills
Strong proficiency in Python and microservice development.Hands-on experience with Claude Code, GitHub Copilot, and prompt engineering.Expertise in LangChain, LangGraph, LangFlow, and agent-based architectures.Solid understanding of software design principles, DDD, and cloud-native architectures.Experience building AI solutions integrated with enterprise APIs.Preferred Skills
Familiarity with AWS services (Bedrock, Lambda, S3, DynamoDB, Postgres/PGVector).Knowledge of containerization (Docker) and CI/CD pipelines.Experience with vector databases, embedding models, and LLM fine-tuning.Understanding of AI governance, bias mitigation, and responsible AI frameworks.Proficiency with FastAPI, LangChain, LangGraph, Bedrock, Anthropic APIs.Experience with observability tools for AI workflows.
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Vacancy posted 1 hour ago
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