Backend Developer (AI Systems)
KODA Kollectiv
Job Title : Backend Developer (AI Systems)
Salary : Php 25,000-75,000
Work Setup : Remote
Employment Type : Contractual
About the Role:
We are looking for a Backend Developer (AI Systems) who can build the APIs, infrastructure, and backend services that power modern AI-enabled applications.
This role focuses on designing scalable backend architectures, integrating AI platforms, and developing systems that support embeddings, vector search, Retrieval-Augmented Generation (RAG), knowledge retrieval, and intelligent automation workflows.
You will work closely with AI engineers, frontend developers, product teams, and stakeholders to create reliable backend foundations that enable AI-powered experiences across web, mobile, and enterprise applications.
Key Responsibilities:
- Design, develop, and maintain scalable backend applications, APIs, and microservices
- Build and manage infrastructure that powers AI-enabled applications and services
- Develop RESTful and GraphQL APIs that integrate with frontend applications, third-party platforms, and AI services
- Implement AI-related backend workflows including embeddings generation, vector search, semantic retrieval, and Retrieval-Augmented Generation (RAG) pipelines
- Integrate AI platforms such as OpenAI, Anthropic Claude, Google AI (Gemini), Azure OpenAI, or similar services
- Design and optimize data pipelines that support AI processing, knowledge retrieval, and intelligent automation
- Build and maintain systems for document ingestion, indexing, chunking, and retrieval workflows
- Work with vector databases and search technologies to improve AI relevance and response quality
- Optimize backend performance, scalability, reliability, and security
- Collaborate with AI engineers and product teams to design AI-driven solutions and workflows
- Monitor, troubleshoot, and improve production systems and backend infrastructure
- Create and maintain technical documentation for APIs, services, and AI architectures
Requirements:
- Strong backend development experience using technologies such as Node.js, NestJS, Laravel, ASP.NET Core, Python, Go, Java, or similar frameworks
- Experience designing and building scalable APIs and distributed systems
- Strong understanding of database design, data modeling, and backend architecture principles
- Experience integrating AI APIs and services into production applications
- Familiarity with embeddings, vector search, semantic retrieval, and Retrieval-Augmented Generation (RAG) concepts
- Experience working with relational and NoSQL databases
- Strong understanding of cloud infrastructure, deployment, and DevOps fundamentals
- Familiarity with AWS, Azure, Google Cloud Platform, or equivalent cloud services
- Understanding of authentication, authorization, security, and API best practices
- Strong debugging, problem-solving, and performance optimization skills
- Good communication skills and ability to work cross-functionally
Nice to Have (Optional):
- Experience with vector databases such as Pinecone, Weaviate, Qdrant, Chroma, Milvus, or similar technologies
- Familiarity with AI orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, CrewAI, or similar tools
- Experience building Retrieval-Augmented Generation (RAG) solutions in production environments
- Experience with event-driven architectures, message queues, and streaming platforms (Kafka, RabbitMQ, SQS, etc.)
- Knowledge of containerization and orchestration technologies such as Docker and Kubernetes
- Experience implementing AI workflows, intelligent agents, or automation platforms
- Familiarity with monitoring and observability tools such as Datadog, Grafana, Prometheus, or Sentry
- Experience supporting AI-powered SaaS, enterprise, or customer-facing applications
What You Can Expect:
- Ownership Impact: Build the core infrastructure and services that enable AI-powered products and experiences
- AI-Driven Work: Work on cutting-edge backend systems supporting intelligent applications and automation workflows
- Technical Challenges: Design scalable architectures for embeddings, vector search, RAG, and AI processing pipelines
- Collaborative Environment: Partner with AI engineers, frontend developers, DevOps engineers, and product teams
- Fast-Paced Execution: Work in an environment that values innovation, ownership, and continuous improvement
- Career Growth: Expand your expertise in backend engineering, AI infrastructure, cloud technologies, and modern distributed systems
Note:
This role focuses on building the backend systems and infrastructure that enable AI-powered applications. Deep machine learning research or model training experience is not required. Candidates with strong backend engineering experience and an interest in AI systems, embeddings, vector search, and Retrieval-Augmented Generation (RAG) are highly encouraged to apply.