Description
We are looking for an AI Developer to build and maintain AI-powered products and services. This role requires strong hands-on ability across LLM applications, backend development, data handling, and practical AI implementation.
The ideal candidate should be able to take requirements, design workable solutions, and deliver production-ready features. They should also have a solid understanding of broader AI concepts beyond prompt engineering, including model training fundamentals, data science basics, and awareness of newer developments in the AI ecosystem.
Key Responsibilities:
- Design and implement AI-powered product features using modern AI and LLM-based approaches.
- Build and maintain backend AI services and APIs using Python and FastAPI.
- Familiarity with tensorflow/pyTorch and huggingface ecosystem.
- Develop prompt workflows for structured, reliable, and high-quality outputs.
- Build workflows involving tool use, orchestration, validation, retries, and agent-style execution.
- Integrate AI features with application backends, databases, internal services, and external APIs.
- Work on use cases such as summarization, search, retrieval, document Q&A, workflow automation, and chatbot-style systems.
- Prepare and process data for AI use cases, including cleaning, chunking, transformation, labeling, and metadata handling.
- Work with PostgreSQL or similar relational databases for storage, retrieval, and AI-related application logic.
- Support model-related tasks such as dataset preparation, fine-tuning workflows, evaluation, and training pipeline support where needed.
- Improve AI quality through prompt refinement, testing, guardrails, and evaluation methods.
- Keep up with relevant AI developments, frameworks, and emerging patterns such as agent ecosystems, MCP, tools/skills-based architectures, and related integration standards.
- Monitor and troubleshoot AI systems for quality, latency, failures, and cost.
- Collaborate with product, backend, and frontend teams to ship end-to-end features.
- Document implementations clearly and follow maintainable engineering practices.
Preferred Qualifications :
Experience with production use of OpenAI or comparable LLM platforms.
- Familiarity with embeddings, vector search, semantic retrieval, and RAG workflows.
- Experience with agent-style workflows, orchestration patterns, multi-step pipelines, or tool-calling systems.
- Awareness of recent AI ecosystem developments such as MCP, tools/skills patterns, and evolving agent integration approaches.
- Experience with batch jobs, background workers, schedulers, or queue-based processing.
- Familiarity with Docker and containerized deployments.
- Exposure to AWS or similar cloud platforms.
- Understanding of AI observability, token usage, and cost-aware implementation.
- Experience contributing to technical design and solution planning.
