Python Developer

Omm IT Solutions

17h•Onsite

About The Position

Ensure chatbot reliability, safety, and compliance through moderation, guardrails, and abuse prevention. Implement monitoring, logging, and alerting to support production reliability and rapid issue resolution. Design and analyze A/B tests to evaluate the impact of changes to chatbot prompts, models, or features. Lead code reviews and enforce best practices to maintain high engineering standards. Contribute to CI/CD pipelines, cloud deployments, and infrastructure decisions supporting high availability. Evaluate and adopt new AI technologies and architectural improvements to support long-term scalability. Be proactive, adaptable, and highly engaged – communicate clearly, raise risks early, and collaborate effectively to deliver high-quality code at speed. Communicate with stakeholders and support user feedback. Design, implement, and maintain relational and/or NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB) to support chatbot functionality, session management, and knowledge base storage. Optimize database queries and ensure data integrity, security, and scalability. Manage document indexing and updates in the knowledge base to ensure accurate and efficient retrieval.

Requirements

Bachelor's Degree in Computer Science, Mathematics, Engineering or a related field.
Masters or Doctorate degree may substitute for required experience
10+ years of experience building, scaling, and maintaining production-grade Python applications.
Deep expertise building, scaling, and maintaining production-grade Python applications.
Understanding of encryption, secure data storage, and transmission (SSL/TLS).
Experience implementing secure login systems (e.g., OAuth2, SAML, Multi-Factor Authentication).
Experience with testing frameworks.
Experience with relational (PostgreSQL, MySQL) and/or NoSQL databases (MongoDB).
Familiarity with automated deployment tools (e.g., Jenkins, GitHub Actions).
Strong Python backend engineering experience including API design, asynchronous programming, and system integration.
Ability to write clear technical documentation for maintainability and compliance.
Proficiency in managing and querying both relational databases and vector databases for semantic search.
Hands-on experience working with AI and LLMs in production environments.
Solid understanding of key AI/LLM concepts, including prompt engineering, RAG, AI agents, context management, evaluation and structured outputs.
Understanding of how to measure LLM performance using frameworks like Ragas, TruLens, or Arize Phoenix to evaluate faithfulness, relevance, and safety.
Demonstrated ability to solve complex technical problems and make sound architectural decisions in ambiguous environments.
Strong communication skills with a proven ability to be vocal, engaged, collaborative, proactive, and adaptable within cross-functional teams.

Nice To Haves

Experience with DevOps practices, including CI/CD pipelines, cloud infrastructure, containerization, monitoring, and logging.
Prior experience building or operating public-facing, high-availability, or regulated systems.
Analyze logs and user interactions to identify usage patterns, common queries, and areas for improvement.
Provide recommendations for enhancements based on data analysis to improve chatbot reliability, accuracy, and user experience.
Familiarity with AI safety, moderation, and responsible AI practices.
Experience working in fast paced, “startup-like" environments.

Responsibilities

Ensure chatbot reliability, safety, and compliance through moderation, guardrails, and abuse prevention.
Implement monitoring, logging, and alerting to support production reliability and rapid issue resolution.
Design and analyze A/B tests to evaluate the impact of changes to chatbot prompts, models, or features.
Lead code reviews and enforce best practices to maintain high engineering standards.
Contribute to CI/CD pipelines, cloud deployments, and infrastructure decisions supporting high availability.
Evaluate and adopt new AI technologies and architectural improvements to support long-term scalability.
Be proactive, adaptable, and highly engaged – communicate clearly, raise risks early, and collaborate effectively to deliver high-quality code at speed.
Communicate with stakeholders and support user feedback.
Design, implement, and maintain relational and/or NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB) to support chatbot functionality, session management, and knowledge base storage.
Optimize database queries and ensure data integrity, security, and scalability.
Manage document indexing and updates in the knowledge base to ensure accurate and efficient retrieval.