Note: The job is a remote job and is open to candidates in USA. Harnham is hiring a Backend AI Engineering Lead to design and build production-grade AI-powered applications and services. The role focuses on backend architecture, Java development, LLMs, generative AI, agentic systems, RAG applications, integrations, and production deployment, while providing technical leadership and mentoring.
Responsibilities
- Design and develop scalable backend services and AI-powered applications, primarily using Java
- Build and integrate applications using LLMs, generative AI, and agentic architectures
- Design AI workflows capable of interacting with APIs, tools, services, and external systems
- Develop RAG-based applications, retrieval workflows, and intelligent search capabilities
- Integrate LLM APIs and AI services into existing software platforms
- Design backend APIs and services that support AI-powered products and workflows
- Take AI concepts and prototypes through technical validation, implementation, and production deployment
- Evaluate emerging AI technologies and frameworks and determine how they can be applied to real-world engineering problems
- Work with existing production systems and integrate new AI capabilities without compromising reliability or maintainability
- Design solutions with scalability, security, performance, observability, and reliability in mind
- Collaborate with engineering and product stakeholders to translate ambiguous requirements into practical technical solutions
- Provide technical leadership through architecture, design reviews, code reviews, and mentoring
- Help establish engineering patterns and best practices for building production AI applications
Skills
- 10+ years of professional software engineering experience
- Strong Java development experience
- Strong backend engineering experience with modern application architectures
- Experience with Spring Boot, REST APIs, and microservices
- Demonstrated experience building or integrating AI/ML capabilities into software products
- Experience taking projects from prototype through production
- Experience working with existing production platforms and codebases
- Strong understanding of software architecture and distributed systems
- Strong software engineering fundamentals across:
- Automated testing
- CI/CD
- Security
- Monitoring and observability
- Performance and scalability
- Working knowledge of SQL and data-driven applications
- Strong communication and technical problem-solving skills
- Comfortable operating as a hands-on technical leader
- Hands-on experience with several of the following:
- Large Language Models / LLM APIs
- Generative AI application development
- RAG and retrieval-based systems
- Vector databases and semantic search
- Agentic AI architectures
- Multi-step AI workflows
- Tool and function calling
- AI agents interacting with APIs and external systems
- Prompt and context engineering
- LLM orchestration frameworks
- AI application evaluation
- AI observability and monitoring
- AI security and guardrails
- Model inference and integration
- Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Spring AI, LangChain4j, or comparable technologies is valuable
- Experienced backend engineers who have moved into applied AI engineering
- You should be able to take an ambiguous AI use case, determine the appropriate technical approach, build the underlying application and integrations, and ultimately deliver a production-quality solution
- Experience with one or more of the following is beneficial:
- Python
- FastAPI
- Cloud platforms
- Docker / Kubernetes
- Event-driven architectures
- Distributed systems
- Data pipelines and data services
- ML/AI development workflows
- Model deployment and inference
- AI evaluation frameworks
Benefits
- Remote work — United States
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