Functional Responsibilities:

• Architect, design, and implement backend systems that integrate with LLMs, and ensure services are scalable, secure, and production-ready
• Implement agentic architectures for complex AI workflows.
• Build, deploy, and manage cloud-native AI applications on AWS (Lambda, ECS, SageMaker) and other modern infrastructure.
• Fine-tune prompts and build RAG pipelines to optimize performance.
• Implement AI security guardrails and conduct risk assessments to ensure compliance, privacy, and safety.
• Monitor application health with observability tools (APM, logging, LLM performance metrics) and proactively resolve performance issues.
• Collaborate with ML Engineers, product managers, and cross-functional teams to understand requirements and deliver AI features that drive measurable value.
• Communicate technical architecture and trade-offs clearly to stakeholders at all levels.
• Contribute to raisingengineeringstandards through code review and knowledge sharing.

Qualifications:

• 5+ years of professional experience as a Software Engineer or in a related role, with a strong foundation in Python.
• Hands-on experience or strong interest in Generative AI frameworks such as LangGraph, LangChain, OpenAI, and RAG implementations.
• Experience with cloud platforms like AWS, including building, deploying, and managing cloud-native applications; exposure to Azure or GCP is also valuable.
• Experience designing and developing APIs using frameworks like FastAPI, Django, or Flask; willingness to learn best practices for scalable production systems is appreciated.
• Strong system design and problem-solving skills, including building, testing, and optimizing backend systems or AI workflows.
• Practical experience with databases (PostgreSQL or NoSQL), and vector databases for RAG workflows.
• Proficiency with DevOps and CI/CD tools such as Docker, Kubernetes, Terraform, and Git-based workflows.
• Understanding of deep learning model development and deployment, with familiarity using frameworks like PyTorch or HuggingFace; motivated learners are welcome.
• Excellent English communication skills, both written and spoken, with the ability to collaborate effectively with global teams and explain complex AI concepts clearly.
• Comfortable translating between technical and business perspectives and managing ambiguous requirements.
• A growth mindset and genuine interest in learning and applying new AI/ML techniques to real-world challenges.