Requirements

• Professional software engineering experience with a strong track record of designing, building, and delivering scalable enterprise-grade solutions in commercial production environments.
• Expert-level proficiency in Python, including its ecosystem for AI/ML development, data engineering, and backend services; full-stack development experience is a plus.
• Extensive hands-on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks (e.g., LangChain, LangGraph, Google ADK, optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel).
• Deep comfort and practical experience with containers and orchestration technologies, specifically OpenShift.
• Demonstrated ability to architect, develop, and deploy highly performant, large-scale AI/ML systems into production.
• Strong understanding of modern software development principles, clean code practices, data structures, algorithms, and distributed systems.
• Proficiency with relational databases (preferably PostgreSQL) and vector databases (preferably pgvector).

Nice to Haves

• Proficiency in additional programming languages such as Java, JavaScript/TypeScript, or Golang.
• Experience with frameworks like Spring (AI, Boot), N8N, or Flask.
• Familiarity with messaging and integration platforms such as Kafka or JMS/MQ.
• Experience with UI development using modern frameworks like React JS or StreamLit for interactive AI applications.
• Practical experience in model risk management, developing AI guardrails, and establishing end-user adoption pathways for Generative AI solutions.
• Proven track record contributing to open-source projects or publishing relevant AI/ML research.

What You'll Be Doing

• Architecting and building production systems by leading hands-on development of sophisticated Generative AI applications, LLM-powered solutions, and agentic frameworks primarily using Python.
• Designing and implementing intelligent agents to automate complex workflows, enhancing efficiency and reducing operational risk at scale.
• Deploying and managing applications within containerized OpenShift environments.
• Driving technical strategy and roadmap for Generative AI adoption, influencing architectural decisions and technology choices.
• Championing software engineering best practices—robust testing, code reviews, documentation, and continuous integration/delivery—to ensure high-quality, mission-critical production systems.
• Innovating and researching new models, techniques, and frameworks in Generative AI, using AI-assisted development tools like Devin and Copilot.
• Mentoring junior engineers and collaborating with cross-functional teams, product managers, and stakeholders.
• Working in an agile environment focused on rapid delivery, iterative development, and agility with a focus on measurable business value and production readiness.
• Ensuring responsible AI by designing robust guardrails and ethical considerations to mitigate risks in accordance with organizational and regulatory standards.

Perks and Benefits

• Opportunity to impact and gain visibility through high-profile projects transforming a global enterprise.
• Access to cutting-edge Generative AI models, agentic frameworks, cloud-native tech, and AI-assisted tools like Devin and Copilot.
• Culture of continuous learning, mentorship, and innovation with resources such as Udemy for Business and Pluralsight.
• Collaborative, passionate team environment that values intellectual curiosity and shared success.
• Flexible hybrid work model with three days in the office and up to two days working from home.
• Work on solutions at a global scale impacting users and operations worldwide.