ConvergeHEALTH-Full-Stack Software Engineer-Innovation_Delivery_Transformation
As a GenAI Full-Stack Application Engineer on the Converge for Health Care team, you will:
- Design and implement full-stack applications using Angular or React on the front end and Node.js and Python-based services on the backend.
- Design and build agentic AI systems, including multi-agent coordination, tool invocation workflows, memory/state management, and structured reasoning pipelines.
- Implement AI-powered components such as RAG pipelines, embedding workflows, vector store integrations, and orchestration layers that connect LLMs to enterprise data and services.
- Deploy AI-enabled applications in AWS environments, leveraging managed services such as ECS/EKS, Lambda, S3, and Bedrock, while applying cloud-native infrastructure patterns to support scalable, production-grade systems.
- Integrate and operate open-source technologies across the stack, including model serving frameworks, vector databases, orchestration libraries, and containerized infrastructure components.
- Containerize and orchestrate services using Docker and Kubernetes to ensure portability, reliability, and scalability across environments.
- Integrate SQL, NoSQL, and vector databases to support high-performance inference, retrieval, and analytics workflows.
- Apply robust testing, logging, monitoring, and observability practices to ensure performance, reliability, and secure AI deployment.
- Collaborate with product managers, data scientists, and healthcare or life sciences domain experts to rapidly prototype, iterate, and harden AI-driven capabilities.
- Participate in agile delivery cycles and contribute to architecture and engineering best practice evolution across the studio.
- Strong working knowledge of both JavaScript/TypeScript and Python in production environments.
- Practical experience building and deploying cloud-native applications in AWS, with familiarity across compute, storage, API, and managed AI services.
- Hands-on experience designing or experimenting with agentic systems using frameworks such as LangChain, LangGraph, CrewAI, Strands, LlamaIndex, DSPy, or similar.
- Working understanding of multi-agent coordination patterns, tool integration, memory persistence, and structured reasoning workflows.
- Familiarity with vector databases and embedding-based retrieval strategies in RAG architectures.
- Comfort working across open-source ecosystems beyond models, including orchestration libraries, model serving stacks, vector stores, observability tooling, and modern infrastructure frameworks.
- Forward-thinking engineering mindset, including embracing AI-enabled development tools (e.g., Claude Code, GitHub Copilot) as productivity multipliers.
- Experience working effectively with globally distributed engineering teams across international time zones.
- Strong debugging, experimentation, and system-level thinking in distributed cloud-native environments.
- Familiarity with healthcare or life sciences industry concepts and data domains (e.g., claims, FHIR, EDI, remittance data, clinical datasets)
- Intellectual curiosity and bias toward building, testing, and iterating quickly in ambiguous environments.
- Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field
- 2+ years of experience building front-end applications using Angular or React
- 2+ years of experience developing backend services using Node.js and/or Python
- 1+ years of experience working with SQL and NoSQL databases
- 1+ years of experience containerizing and orchestrating applications using Docker and Kubernetes
- 1+ years of experience implementing application security controls across services and data stores
- Ability to travel up to 10%, on average, based on client and project needs
- Must be legally authorized to work in the United States without employer sponsorship
- Master's degree in Computer Science, Engineering, Artificial Intelligence, or related field
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