This is a remote position.
Key Responsibilities
- Design and develop agent-based systems capable of multi-step reasoning planning and tool usage.
- Build and deploy LLM-powered applications including autonomous agents workflows and decision-making systems.
- Implement tool-calling frameworks enabling agents to interact with APIs databases and external services.
- Design memory systems for agents including short-term context long-term memory and retrieval mechanisms.
- Build orchestration layers for multi-agent systems ensuring coordination retries and failure handling.
- Develop Retrieval-Augmented Generation (RAG) pipelines using embeddings vector databases and structured data sources.
- Design and optimize prompt engineering strategies for reliability consistency and performance.
- Build backend services (Python / / Go) to support agent execution workflow management and system integration.
- Develop APIs and microservices to expose agent capabilities to frontend applications and external systems.
- Integrate vector databases (e.g. Pinecone Weaviate Milvus Qdrant) for semantic search and contextual retrieval.
- Implement evaluation frameworks to measure agent performance accuracy and reliability.
- Ensure safety guardrails and structured output validation for production AI systems.
- Collaborate with product and engineering teams to translate business requirements into agentic workflows.
Requirements
- 38 years of experience in Software Engineering or AI Engineering
- Strong backend development skills (Python / / Go)
- Experience with LLMs and agent frameworks (e.g. tool-calling function calling orchestration systems)
- Experience building or working with RAG systems
- Familiarity with vector databases (Pinecone Qdrant Milvus Weaviate etc.)
- Strong understanding of APIs distributed systems and microservices
- Experience with cloud platforms (AWS GCP or Azure)
- Knowledge of databases (PostgreSQL MongoDB etc.)
- Understanding of system design and scalable architecture
Nice to Have
- Experience with multi-agent systems or autonomous workflows
- Experience with prompt optimization and evaluation frameworks
- Knowledge of observability for AI systems (logging tracing evaluation pipelines)
- Experience deploying AI systems in production environments
- Familiarity with Kubernetes and containerized deployments
- Understanding of caching queues and distributed processing systems
What Youll Do
- Build next-generation autonomous AI systems that can reason plan and execute tasks
- Design intelligent workflows powered by LLMs and external tools
- Develop scalable backend systems supporting agent execution at production scale
- Contribute to architecture decisions for AI infrastructure and orchestration layers
- Improve reliability safety and performance of agent-based systems
- Work closely with product and engineering teams to bring AI-driven features into production
Required Skills:
Key Responsibilities Design develop and maintain robust scalable and secure Java applications Build and optimize RESTful APIs and microservices architecture Collaborate with cross-functional teams (product QA DevOps) to deliver features Write clean efficient and well-documented code Perform code reviews and mentor junior developers Troubleshoot debug and improve system performance Participate in architectural discussions and technical decision-making Ensure application security scalability and reliability Required Skills & Qualifications Strong proficiency in Java (8 or above) Experience with Spring Framework / Spring Boot Solid understanding of object-oriented programming (OOP) principles Experience with REST APIs Microservices architecture Knowledge of SQL and NoSQL databases (e.g. MySQL PostgreSQL MongoDB) Familiarity with version control systems (Git) Experience with CI/CD pipelines and build tools (Maven/Gradle) Understanding of cloud platforms (AWS Azure or GCP) is a plus Strong problem-solving and analytical skills Preferred Qualifications Experience with Docker Kubernetes Knowledge of event-driven architecture (Kafka RabbitMQ) Exposure to performance tuning and system design Prior experience in Agile/Scrum environments Soft Skills Strong communication and collaboration skills Ability to work independently and take ownership Mentorship mindset and leadership qualities
This is a remote position.Key Responsibilities Design and develop agent-based systems capable of multi-step reasoning planning and tool usage. Build and deploy LLM-powered applications including autonomous agents workflows and decision-making systems. Implement tool-calling frameworks enabling a...
This is a remote position.
Key Responsibilities
- Design and develop agent-based systems capable of multi-step reasoning planning and tool usage.
- Build and deploy LLM-powered applications including autonomous agents workflows and decision-making systems.
- Implement tool-calling frameworks enabling agents to interact with APIs databases and external services.
- Design memory systems for agents including short-term context long-term memory and retrieval mechanisms.
- Build orchestration layers for multi-agent systems ensuring coordination retries and failure handling.
- Develop Retrieval-Augmented Generation (RAG) pipelines using embeddings vector databases and structured data sources.
- Design and optimize prompt engineering strategies for reliability consistency and performance.
- Build backend services (Python / / Go) to support agent execution workflow management and system integration.
- Develop APIs and microservices to expose agent capabilities to frontend applications and external systems.
- Integrate vector databases (e.g. Pinecone Weaviate Milvus Qdrant) for semantic search and contextual retrieval.
- Implement evaluation frameworks to measure agent performance accuracy and reliability.
- Ensure safety guardrails and structured output validation for production AI systems.
- Collaborate with product and engineering teams to translate business requirements into agentic workflows.
Requirements
- 38 years of experience in Software Engineering or AI Engineering
- Strong backend development skills (Python / / Go)
- Experience with LLMs and agent frameworks (e.g. tool-calling function calling orchestration systems)
- Experience building or working with RAG systems
- Familiarity with vector databases (Pinecone Qdrant Milvus Weaviate etc.)
- Strong understanding of APIs distributed systems and microservices
- Experience with cloud platforms (AWS GCP or Azure)
- Knowledge of databases (PostgreSQL MongoDB etc.)
- Understanding of system design and scalable architecture
Nice to Have
- Experience with multi-agent systems or autonomous workflows
- Experience with prompt optimization and evaluation frameworks
- Knowledge of observability for AI systems (logging tracing evaluation pipelines)
- Experience deploying AI systems in production environments
- Familiarity with Kubernetes and containerized deployments
- Understanding of caching queues and distributed processing systems
What Youll Do
- Build next-generation autonomous AI systems that can reason plan and execute tasks
- Design intelligent workflows powered by LLMs and external tools
- Develop scalable backend systems supporting agent execution at production scale
- Contribute to architecture decisions for AI infrastructure and orchestration layers
- Improve reliability safety and performance of agent-based systems
- Work closely with product and engineering teams to bring AI-driven features into production
Required Skills:
Key Responsibilities Design develop and maintain robust scalable and secure Java applications Build and optimize RESTful APIs and microservices architecture Collaborate with cross-functional teams (product QA DevOps) to deliver features Write clean efficient and well-documented code Perform code reviews and mentor junior developers Troubleshoot debug and improve system performance Participate in architectural discussions and technical decision-making Ensure application security scalability and reliability Required Skills & Qualifications Strong proficiency in Java (8 or above) Experience with Spring Framework / Spring Boot Solid understanding of object-oriented programming (OOP) principles Experience with REST APIs Microservices architecture Knowledge of SQL and NoSQL databases (e.g. MySQL PostgreSQL MongoDB) Familiarity with version control systems (Git) Experience with CI/CD pipelines and build tools (Maven/Gradle) Understanding of cloud platforms (AWS Azure or GCP) is a plus Strong problem-solving and analytical skills Preferred Qualifications Experience with Docker Kubernetes Knowledge of event-driven architecture (Kafka RabbitMQ) Exposure to performance tuning and system design Prior experience in Agile/Scrum environments Soft Skills Strong communication and collaboration skills Ability to work independently and take ownership Mentorship mindset and leadership qualities
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