LatentBridge
Website:
latentbridge.com
Job details:
About the RoleWe are seeking a highly skilled First Party Claude Engineer with 6–8 years of software engineering experience and hands-on expertise in building enterprise-grade Generative AI applications using the Anthropic Claude ecosystem.
The ideal candidate will be responsible for developing, integrating, optimizing, and maintaining Claude-powered AI applications and services. This role requires strong engineering capabilities in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, cloud platforms, and production-grade AI deployments.
You will collaborate with AI architects, product managers, platform engineers, and business teams to build scalable, secure, and high-performing AI solutions.
RequirementsKey Responsibilities
- Develop and maintain enterprise AI applications powered by Anthropic Claude models.
- Design, build, and optimize inference pipelines for production AI workloads.
- Integrate Claude APIs into enterprise applications and backend systems.
- Design and implement Retrieval-Augmented Generation (RAG) solutions using vector databases.
- Build AI agents and agentic workflows using modern orchestration frameworks.
- Develop scalable backend services and REST APIs using Python.
- Implement prompt engineering strategies for different business use cases.
- Optimize AI application performance for latency, throughput, reliability, and cost.
- Build reusable AI components, libraries, and integration frameworks.
- Collaborate with cross-functional teams to translate business requirements into technical solutions.
- Integrate AI applications with enterprise systems, APIs, and databases.
- Implement monitoring, logging, evaluation, and observability for AI applications.
- Troubleshoot production issues and continuously improve platform performance.
- Follow enterprise security, governance, and responsible AI best practices.
- Participate in code reviews, technical discussions, and architecture planning.
Required Skills & Qualifications
- 6–8 years of experience in Software Engineering or Backend Development.
- Minimum 2 years of hands-on experience working with Large Language Models (LLMs) and Generative AI.
- Strong hands-on experience with Anthropic Claude APIs and enterprise AI integrations.
- Proficiency in Python.
- Experience building REST APIs using FastAPI, Flask, or similar frameworks.
- Strong understanding of:
- Large Language Models (LLMs)
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Agents and Agentic Workflows
- Embeddings and Semantic Search
- Experience with AI orchestration frameworks such as:
- LangChain
- LangGraph
- Semantic Kernel
- Experience working with vector databases such as:
- Pinecone
- ChromaDB
- Weaviate
- Milvus
- FAISS
- Experience integrating AI applications with enterprise platforms and APIs.
- Good understanding of cloud platforms such as Microsoft Azure or Amazon Web Services (AWS).
- Familiarity with Git, Docker, Kubernetes, and CI/CD pipelines.
- Strong analytical, debugging, and problem-solving skills.
- Excellent communication and collaboration abilities.
Preferred Skills
- Experience building AI copilots or conversational AI solutions.
- Experience developing multi-agent AI systems.
- Familiarity with Model Context Protocol (MCP).
- Experience with Azure AI Foundry or Azure OpenAI Services.
- Knowledge of AI evaluation and observability tools such as Langfuse, Phoenix, or OpenTelemetry.
- Exposure to Redis, Kafka, or event-driven architectures.
- Understanding of AI guardrails, responsible AI, and enterprise security practices.
- Experience with DevOps and MLOps concepts for AI deployments.
Technical Skill SetProgramming Languages
AI & Generative AI
- Anthropic Claude
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Agents
- LangChain
- LangGraph
- Semantic Kernel
Backend Technologies
- FastAPI
- Flask
- REST APIs
- Microservices
Databases
- PostgreSQL
- Pinecone
- ChromaDB
- Weaviate
- Milvus
- FAISS
Cloud Platforms
- Microsoft Azure
- Amazon Web Services (AWS)
DevOps & Tools
- Git
- Docker
- Kubernetes
- CI/CD Pipelines
Monitoring & Observability
- Langfuse
- OpenTelemetry
- Phoenix (Preferred)
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Master's degree is an advantage but not mandatory.
Preferred Certifications
- Azure AI Engineer Associate (AI-102)
- Azure Fundamentals (AZ-900)
- AWS Certified Machine Learning – Specialty (Preferred)
- Anthropic Claude Certification or equivalent Generative AI certification (Preferred)
Click on Apply to know more.
