Specialist Software Engineer - AI Systems
Core
Design, configure, and build agentic AI systems, cloud-native software applications, and ML-enabled solutions leveraging large language models and intelligent agents.
Role type
Senior Software Engineer (AI Systems)
Builds
Scalable software systems integrating LLMs, agent frameworks, RAG patterns, and MLOps for enterprise use.
Domain
Biotechnology / Generative AI / Cloud Native
Deliverable
production ML models | product features | infrastructure
Required skills
Python, JavaScript/TypeScript, SQL/NoSQL, Cloud-native development, LLM integration, Agent frameworks, RAG patterns, MLOps, CI/CD, Containerization, Observability
Preferred skills
LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, Vector databases, Embeddings, Semantic search, Reranking, Prompt engineering, Fine-tuning, LLM evaluation, MLOps tools (MLflow, SageMaker, Databricks, Kubeflow, Airflow), Kubernetes, Serverless, Microservices, Event-driven architecture, Responsible AI, Model governance
Technologies
AWS, LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, MLflow, SageMaker, Databricks, Kubeflow, Airflow, Kubernetes
Responsibilities
Design and build agentic AI systems that reason, plan, and execute workflows; Develop scalable cloud-native applications; Integrate LLMs, APIs, databases, and vector stores; Build AI workflows using agent frameworks; Implement RAG patterns for document ingestion and response generation; Partner with data science teams to operationalize ML models; Apply MLOps for deployment and monitoring; Develop reusable components and integration patterns; Define cloud architectures on AWS; Implement observability and performance optimization; Evaluate and improve agent performance metrics.
Seniority
Senior, hands-on IC